Artificial Intelligence (AI),
Impressive, but Imperfect
November 5, 2025, 12noon PT at SIR, Branch 51
Los Altos Hills Country Club (Host: Steve Tremulis)
Presentations online at: https://slideshare.net/spohrer
Jim Spohrer
Retired Industry Executive (Apple, IBM)
Board of Directors (ISSIP, ServCollab)
UIDP Senior Fellow
Questions: spohrer@gmail.com
BlueSky: @spohrer.bsky.social
LinkedIn: https://www.linkedin.com/in/spohrer/
English: https://youtu.be/T4S0uZp1SHw
French: https://youtu.be/02hCGRJnCoc
https://answersfrom.me/jimtwin
•https://youtu.be/PnmVqASd1VE
Lee Nackman (retired IBM) – Thinking
AI
As I was preparing this talk….
• Some words kept going thru my mind from
Arbesman (2025)…
• Chapter 8: Tools for Thought: Software for
Thinking.
• “Too often technology is at odds with
humanity...
For example... QWERTY...
... we have, by and large, adapted ourselves to
technology in ways that are not good for us.
Our increased drive for optimization of work
can run directly counter to our ability to think
deeply, or to even feel that human.”
And this book as well…
• Property
• All social problems seem rooted
in three types of property
• Noncoercion
• Freedom
• Gratitude
• Need for cultural evolution
• to avoid coercion in any form.
• https://progressisachoice.net
Who am I?
Jim Spohrer
1956
Maine
1974
MIT
1978
Verbex –
startup AI
company
1982
Yale
1989
University of
Rome La
Sapienza, Italy
1989
Apple
1998
IBM
2021
Retired (help
non-profits
with an eye to
the future of
service & AI :
ISSIP,
ServCollab,
UIDP)
Questions for SIRs (Seniors) at Dawn of AI Era:
All generations need good answers to these questions.
Q1: What would you do if you have 100 highly skilled
workers working for you (e.g., software development,
marketing, etc.)?
Q2: What job(s) would you assign to (if you had one)
your AI Digital twin?
Q3: What is the best way(s) that you know of to keep up
with accelerating change?
Optimistic Realistic
Knowing
Doing
How to keep up with accelerating change? Follow a diverse collection of people… make up dimensions meaningful to you!
Sadly for me… my brain is biased into thinking I can understand older, white, males the best… maybe AI can help overcome!
TheNeuron
Who do
I wish I had
Accurate,
Up-to-date
AI Digital
Twins of?
The Neuron
Today’s Talk:
• Past
• 1947, 1958, 1971
• Present
• 70, 35000, 250000
• Future
• Solution to 3 Es
• TBD – your AI digital twin?
1947
1958
1971 2024
1947
Transistor
Bell Labs
1958
Integrated Circuit
Texas Instrument
1971
Microprocessor
Intel
2024
H100
NVidia
Challenges: How to prepare for the next wayes of innovations, including
digital twins and humanoid robots, as well as to learn to invest more wisely
(self-control).
As the marginal cost of computing goes to zero, service innovation will go
thru the roof,
and energy consumption will go thru the roof as well…
REMEMBER THESE DATES, FACTS,
CHALLENGES
weight: 70 pounds
complexity: 35,000 parts
cost: 250,000 dollars
1956
2023
2060 2080
1956
First AI
Workshop
2023
ChatGPT 100M
users in just 2
months
(1.5B visits in
Sept)
2060 (Predicted)
Exascale for
$1000
(~ one human
brain)
2080 (Predicted)
Ronnascale for $1B
(~ billion human brains)
Progress in IA (Intelligence Augmentation) for nations can be estimated as
GPD/worker.
Progress in AI (Artificial Intelligence) is directly connected to the cost of
computing.
REVIEW: REMEMBER THESE DATES
Jensen:
You imagine a tiny chip…
The H100 weighs 70 pounds…
35000 parts…
$250K cost…
It replaces a data center…
Full of computers and cables…
Jim:
Driving the marginal cost of
computing to zero…
Drives the demand for new
service offerings based on
computing through the roof
MORE SPOHRER USE CASES:
https://service-science.info/archives/6521
Icons of AI Progress
• 1955-1956: Dartmouth Workshop organized by:
• Two early career faculty
• John McCarthy (Dartmouth, later Stanford)
• Marvin Minsky (MIT)
• Two senior industry scientists
• Claude Shannon (Bell Labs)
• Nathan Rochester (IBM)
• 1997: Deep Blue (IBM) - Chess
• 2011: Watson Jeopardy! (IBM)
• 2016: AlphaGo (Google DeepMinds)
• 2017: All you need is attention (Google) - Transformers
• Attention heads (working memory) to predict what comes next
• 2018: AlphaFold (Google DeepMinds)
• 2020: Language models are few-shot learners (OpenAI)
• 2022: DALL-E 2 & ChapGPT (OpenAI)
• 2022: Constitutional AI (Anthropic) – “Behave yourself!”
• 2023: New Bing+ (Microsoft) & GPT-4 (OpenAI)
• 2024: More & Bigger Models: OpenAI, Microsoft, Google, Anthropic,
etc.
• 2024: Reid Hoffman’s Digital Twin & Unitree’s G1 Humanoid Robot
11/05/2025 Jim Spohrer 15
p://www-formal.stanford.edu/jmc/history/dartmouth/dartmouth.html
https://cdn.openai.com/papers/gpt-4.pdf
1955 2023
1960 1980 2000 2020 2040 2060 2080
1960 1980 2000 2020 2040 2060 2080
$1,000,000,000,000
(Trillion)
$1,000,000
(Million)
$1,000,000,000
(Billion)
$1,000
(Thousand)
$1
Cost
1960 1980 2000 2020 2040 2060 2080
$1,000,000,000,000
(Trillion)
$1,000,000
(Million)
$1,000,000,000
(Billion)
$1,000
(Thousand)
$1
Kiloscale
(10 3
)
M
egascale
(10 6
)
Gigascale
(10 9
)
Terascale
(10 12
)
Petascale
(10 15
)
Exascale
(10 18
)
Zettascale
(10 21
)
Yottascale
(10 24
)
Ronnascale
(10 27
)
Cost of Computation (Diagonals)
1960 1980 2000 2020 2040 2060 2080
$1,000,000,000,000
(Trillion)
$1,000,000
(Million)
$1,000,000,000
(Billion)
$1,000
(Thousand)
$1
Kiloscale
(10 3
)
M
egascale
(10 6
)
Gigascale
(10 9
)
Terascale
(10 12
)
Petascale
(10 15
)
Exascale
(10 18
)
Zettascale
(10 21
)
Yottascale
(10 24
)
Ronnascale
(10 27
)
Cost of Computation (Diagonals)
Note: Adjust Kilo and Mega scales slightly to fit data better (early days – more cost – learning curve).
1960 1980 2000 2020 2040 2060 2080
$1,000,000,000,000
(Trillion)
$1,000,000
(Million)
$1,000,000,000
(Billion)
$1,000
(Thousand)
$1
Gigascale
(10 9
)
Terascale
(10 12
)
Petascale
(10 15
)
Exascale
(10 18
)
Zettascale
(10 21
)
Yottascale
(10 24
)
Ronnascale
(10 27
)
GDP/Employee
Trend
Estimating Knowledge Worker
Productivity
Based on USA
Historical Data
Year Value
1960 $10K
1980 $33K
2000 $78K
2020. $151K
2023 $169K
Kiloscale
(10 3
)
M
egascale
(10 6
)
of computation goes down by 1000x every 20 years (left to right diagonals), driving knowledge worker productivity
22
September 2018 / © 2018 IBM Corporation
Petaflops = 1,000,000,000,000,000 or a million
billion = 10 ** 15
Megaflops = 1,000,000 = million = 10 ** 6
Gigaflops = 1,000,000,000 = billion = 10 ** 9
One of the AI Super Computers in the World,
= 13 MegaWatts of Power (HOT!)
23
September 2018 / © 2018 IBM Corporation
Exascale = 1,000,000,000,000,000,000 or a
billion billion = 10 ** 18
Megaflops = 1,000,000 = million = 10 ** 6
Gigaflops = 1,000,000,000 = billion = 10 ** 9
Human Brain
= 20 Watts (COOL!)
1960 1980 2000 2020 2040 2060 2080
$1,000,000,000,000
(Trillion)
$1,000,000
(Million)
$1,000,000,000
(Billion)
$1,000
(Thousand)
$1
Gigascale
(10 9
)
Terascale
(10 12
)
Petascale
(10 15
)
Exascale
(10 18
)
Zettascale
(10 21
)
Yottascale
(10 24
)
Ronnascale
(10 27
)
GDP/Employee
Trend
Estimating Knowledge Worker
Productivity
Based on USA
Historical Data
Year Value
1960 $10K
1980 $33K
2000 $78K
2020. $151K
2023 $169K
Kiloscale
(10 3
)
M
egascale
(10 6
)
of computation goes down by 1000x every 20 years (left to right diagonals), driving knowledge worker productivity
Predict the Timeline:
GDP/Employee
National Academy - Service Systems and AI 25
(Source)
Lower compute costs translate into increasing productivity and GDP/employees for nations
Increasing productivity and GDP/employees should translate into wealthier citizens
AI Progress on Open Leaderboards
Benchmark Roadmap to solve AI/IA
Alistair Nolan (OECD AI for Science Productivity): “It has been stated that the number of engineers proclaiming the end of Moore's Law doubles every two years.”
Rouse WB, Spohrer JC. (2018) Automating versus augmenting intelligence. Journal of Enterprise Transformation. 2018 Apr 3;8(1-2):1-21.
Read Rouse & Spohrer (2018)
enough to understand this slide
including what ”exascale” means
11/22/22
Part 1: Solving AI
What is an AI digital twin?
• Well, imagine if there was a
“mimic” version of you that was
online 24x7 and could
speak any language, with
knowledge of your publications,
and could explain things in a way
an audience of listeners might
understand?
• ReidAI’s purpose - to challenge
Reid Hoffman in new ways and
experiment with new tech
capabilities
https://youtu.be/rgD2gmwCS10
ReidTwin ReidReal
Who else is getting a twin (AI Avatar)?
• SJSU President
• Cynthia Teniente Matson
• https://youtu.be/gqrIMItHyz8
• “expanding our reach,
and enhancing communications.”
JimTwin Adventure…
• ChatBot (Tmpt.app)
• Scott Zimmer
• https://answersfrom.me/jimtwin
• Avatar-1 (HeyGen.ai)
• SJSU Team (Claude + HeyGen)
• https://youtu.be/T4S0uZp1SHw
• https://youtu.be/02hCGRJnCoc
• Avatar-2 (GitHub)
• Arnay Bhatia
• https://youtu.be/mwnZjTNegXE
• https://youtu.be/QR17aXYgefk
Do you want a digital twin of yourself?
No/Yes/Not Sure
Narayan S & Spohrer J (2025) Metrics, Incentives, Rewards, and Culture for Impact. In
Hall R & Boccanfuso A,Editors, University-Industry Collaboration, Innovation at the
Interface. Springer. URL: https://link.springer.com/book/10.1007/978-3-031-94913-5
Spohrer, J.C. (2010). IBM's University Programs. IEEE Computer 43(8):102-104.
URL: https://service-science.info/wp-content/uploads/2017/04/IBM-GUP-5Rs-copy-2.pdf
Spohrer, J.C. (2013). What's Up at IBM? University Programs! The 6 R's helping to
build a Smarter Planet: Research, Readiness, Recruiting, Revenue, Responsibility,
Regions. May 14, 2013. Slideshare. URL:
https://www.slideshare.net/slideshow/ibm-up-external-20130514-v11/21175603
Spohrer, J. (2017). IBM's service journey: A summary sketch. Industrial
Marketing Management, 60, 167-172.
URL: https://www.sciencedirect.com/science/article/abs/pii/S0019850116301778?via%3Dihub
Spohrer, J. (2024a). AI Upskilling and Digital Twins: A Service Science
Perspective on the Industry 4.0 to Industry 5.0 Shift. In Industry 4.0 to
Industry 5.0: Explorations in the Transition from a Techno-economic to a
Socio-technical Future (pp. 79-92). Singapore: Springer Nature.
URL: https://link.springer.com/chapter/10.1007/978-981-99-9730-5_4
Spohrer, J. (2024b) Personal AI digital twins: the future of human interaction? EIT
Digital URL: https://www.eitdigital.eu/newsroom/grow-digital-insights/personal-ai-digital-twins-the-future-of-human-interaction/
3Es: Challenges to “Humanity-Friendly AI Teammate”
• Energy
• Errors
• Ethics
Hicks MT, Humphries J, Slater J (2024)
ChatGPT is bullshit.
Ethics & Information Technology 26(38).
URL: https://doi.org/10.1007/s10676-024-09775-5
IBM Research - TrueNorth (Dharmendra Modha and team)
Pssssssst!
The real problem
is communication
between people.
Can more computation
help?
Why do GenAI LLMs work as well as they do? Honestly, no one
knows for sure.
We see prediction & pattern completion,
but not true reasoning, just mimicry
Impressive performance, but prediction alone is not enough
Imperfect, because human-like reasoning (with world models) is not there
Nevertheless, pattern completion is very good
The answer will require a better understanding of optimization in high dimensional
spaces
The good and the bad
What is AI good at? Speed, Summarization (What is needed to regenerate whole,
stripped of most specifics), Outline content (What the abstract structures are),
Creative Pattern Completion (Fiction – made up details that might seem plausible).
What is AI bad at? 3Es (energy, errors, ethics <- because of how we build it today).
What is surprising?
Surprise! Everything can be near and far at the same time in a high dimensional
space (very similar, very different) – amplifier of consilience and polarization.
Surprise! Every starting point is near a ”black hole” of nearly ideal optimization as
higher and higher dimensions and more and more data are used. (quadrillions of
partial coherent structures)
Impressive, but imperfect
Impressive: The mathematics of high-dimensional optimization work pretty well for
predicting local coherence at multiple scales of patterns ( plausible pattern
completion tasks)
Imperfect: Reasoning requires world models, perhaps multiple mappings from high
dimensional to low dimensional representation spaces preserving certain relations
as world models, or creating Python program world models to help. Generate-Test-
and-Debug (G-T-D) will likely be required with human-like episodic memory with
expectation violations and remindings (Schank’s ”Dynamic Memory” and Case-
Based Reasoning)
HCI to improve HHI
• Teammates, that I know is much better in
my mind….
• Recent Stanford paper – generic AI
teammates
• “It’s the AI PI’s job to figure out the other
agents and expertise needed to tackle the
project,” Zou said. For the SARS-CoV-2
project, for instance, the PI agent created
an immunology agent, a computation
biology agent and a machine learning
agent. And, in every project, no matter the
topic, there’s one agent that assumes the
role of critic. Its job is to poke holes, caution
against common pitfalls and provide
constructive criticism to other agents.”
(1) What would you do
with 100 highly-skilled
workers?
(2) Redo Divide & Conquer
In AI era.
(3) Why real person
in that role?
Because real people
have goals & plans
they prefer.
Real people sleep.
Real rehearse high stakes.
Hot Topic: More Readings Every Day
• Gary Hunnicut suggested (2025)
• “Digital Twins for Cancer—Not If, But When, How, and Why?”
• https://datascience.cancer.gov/news-events/blog/digital-twins-cancer-not-if-when-how-and-why
• Cybernetic Teammates (2025)
• “The Cybernetic Teammate: A Field Experiment on Generative AI Reshaping Teamwork and Expertise”
• https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5188231
• Vendor Policy Brief
• “A Policy Framework for Building the Future of Science with AI”
• https://static.googleusercontent.com/media/publicpolicy.google/en//resources/ai_policy_framework_
science_en.pdf
• ”Towards an AI Co-Scientist” - https://storage.googleapis.com/coscientist_paper/ai_coscientist.pdf
• Humanity (just out today – April 2, 2025)
• Being Human in 2035: How Are We Changing in the Age of AI
• URL:
https://imaginingthedigitalfuture.org/wp-content/uploads/2025/03/Being-Human-in-2035-ITDF-report
.pdf
• Transdisciplinarity (2023)
• "Transdisciplinary Team Science: Transcending Disciplines to Understand Artificial Social Intelligence in
Human-Agent Teaming”
• https://journals.sagepub.com/doi/full/10.1177/21695067231192245
• Augmentation – Amplification (1962)
• “Augmenting Human Intellect: A Conceptual Framework” (cites Licklider 1960 and Bush 1945)
• https://www.dougengelbart.org/pubs/augment-3906.html
Tool, Assistant, Collaborator, Coach, Mediator (“Trust”)
11/05/2025 Understanding Cognitive Systems 34
Task & World Model/
Planning & Decisions
Self Model/
Capacity & Limits
User Model/
Episodic Memory
Institutions Model/
Trust & Social Acts
Tool + - - -
Assistant ++ + - -
Collaborator +++ ++ + -
Coach ++++ +++ ++ +
Mediator +++++ ++++ +++ ++
Cognitive
Tool
Cognitive
Assistant
Cognitive
Collaborator
Cognitive
Coach
Cognitive
Mediator
Part 2: Solving IA = Intelligence Augmentation (in a humanity-friendly way)
Solving IA also requires
All of this and done well
As a “bicycle for the mind”
To make us stronger,
Not weaker
When tech is all removed
Read Demirkan & Spohrer (2025)
enough to understand this slide
including what ”trusted mediator”
means
Demirkan H, Spohrer J (2025) Talent Management: “Here Come the Digital Workers!”.
In ORMS Today, INFORMS, June 17, 2025. URL: https://pubsonline.informs.org/do/10.1287/orms.2025.02.15/full/
The Communication Problem:
In a Nutshell
• Doing More
• Agreeing Less
Can GenAI LLMs help people to stop wasting creative friction?
Competing ideas can lead to “insanely great” win-win collaborations.
If we can figure out communications between people.
Latent spaces for people.
Barile S, Piciocchi P, Saviano M, Bassano C, Pietronudo C, Spohrer JC (2019))
Towards a new logic of value co-creation in the digital age: doing more and agreeing less.
Naples Forum on Service. URL: ttps://tinyurl.com/2019-DoingMoreAgreeingLess
Failure
To Find
Win-Win
Long flights sometimes allow long
conversations
• 1440 News (July 11, 2025): The high-fashion ‘It’ bag origin story
• Birkin (Actress) and Dumas (Fashion Designer) meet
• “The bag’s story began in the 1980s when the actress met Hermès
CEO Jean-Louis Dumas on a flight. Frustrated with her handbag,
Birkin described her ideal bag to Dumas, and they famously
sketched the design on an airsickness bag.”
• URL: https://en.wikipedia.org/wiki/It_bag
• Win-Win Opportunities
• Do Win-Win opportunities always exist between any two actors?
• What are the set of possible Win-Win’s between actors?
• How best to explore the Win-Win possibilities between two
actors?
• How does finding Win-Win opportunities relate to Truth?
Truth, Trust, and Wisdom
• Truth: The ongoing pursuit
• Mathematical, Computational, Empirical,
Historical, Rhetorical
• Knowing a ”better argument” when we see it and
why (humility needed)
• Trust: Hard to build, easy to destroy
• Mental models and predictable behaviors
• AI digital twins of all responsible actors
• Wisdom: Learning to invest wisely
• In becoming better future versions of ourselves
• In a world that future generations will want to
live in together
Resilience:
Rapidly Rebuilding From Scratch
• Dartnell L (2012)
The Knowledge: How to Rebuild Civilization i
n the Aftermath of a Cataclysm.
Westminster London: Penguin Books.
11/05/2025 Jim Spohrer (ISSIP) 38
Part 3: “Solving All Problems”
Two disciplines: Two approaches to the future
Artificial Intelligence is almost seventy-years-old discipline in computer
science that studies automation and builds more capable technological
systems. AI tries to understand the intelligent things that people can do
and then does those things with technology. (https://deepmind.com/about “...
we aim to build advanced AI - sometimes known as Artificial General Intelligence (AGI) - to
expand our knowledge and find new answers. By solving this, we believe we could help
people solve thousands of problems.”)
Service science is an emerging transdiscipline not yet twenty-years- old
that studies transformation and builds smarter and wiser socoi-
technical systems – families, businesses, nations, platforms and other
special types of responsible entities and their win-win interactions that
transform value co-creation and capability co-elevation mechanisms
that build more resilient future versions of themselves – what we call
service systems entities. Service science tries to understand the
evolving ecology of service system entities, their capabilities,
constraints, rights, and responsibilities, and then then seeks to improve
the quality of life of people (present/smarter and future/wiser) in those
service systems.
Artificial Intelligence
Automation
Generations of machines
Service Science
Transformation
Generations of people
(responsible entities)
Service systems are dynamic configurations of people,
technology, organizations, and information, connected
internally and externally by value propositions, to other
service system entities. (Maglio et al 2009)
OpenAI’s Roadmap
Service Science: Conceptual Framework
11/05/2025 (c) IBM MAP COG .| 41
Service Science
(c) IBM MAP COG .| 42
Service Science: Transdisciplinary Framework to Study Service Systems
Systems that focus on flows of things Systems that govern
Systems that support people’s activities
transportation &
supply chain water &
waste
food &
products
energy
& electricity
building &
construction
healthcare
& family
retail &
hospitality banking
& finance
ICT &
cloud
education
&work
city
secure
state
scale
nation
laws
social sciences
behavioral sciences
management sciences
political sciences
learning sciences
cognitive sciences
system sciences
information sciences
organization sciences
decision sciences
run professions
transform professions
innovate professions
e.g., econ & law
e.g., marketing
e.g., operations
e.g., public policy
e.g., game theory
and strategy
e.g., psychology
e.g., industrial eng.
e.g., computer sci
e.g., knowledge mgmt
e.g., statistics
e.g., knowledge worker
e.g., consultant
e.g., entrepreneur
stakeholders
Customer
Provider
Authority
Competitors
resources
People
Technology
Information
Organizations
change
History
(Data Analytics)
Future
(Roadmap)
value
Run
Transform
(Copy)
Innovate
(Invent)
Stackholders (As-Is)
Resources (As-Is)
Change (Might-Become)
Value (To-Be)
43
ECOLOGY
14B
Big Bang
(Natural
World)
10K
Cities
(Human-Made
World)
Sun
writing
(symbols and scribes)
Earth
written laws
bacteria
(uni-cell life)
sponges
(multi-cell life)
money
(coins)
universities
clams (neurons)
trilobites (brains)
printing press (books)
steam engine
200M
bees (social
division-of-labor)
60
transistor
Where is the “Real Science”? Ecology++
Transdisciplinary sciences that study the natural and human-made worlds…
Unraveling the mystery of evolving hierarchical-complexity in new populations…
To discover the world’s structures and mechanisms for computing non-zero-sum
Value-CoCreation (VCC), Diverse Architectures of Holistic Service Systems (HSS)
Sun
Earth
Bacteria
Sponges
Clams
Universe
Cities
Writing
Laws
Money
Universities
We get the future we invest in…
“Service providers
will not be replaced by AI,
but trusted service providers
who use AI (well and responsibly)
will replace those who don’t.”
National Academy - Service Systems and AI 44
Every person in a role in an organization is a service provider.
11/05/2025
“The best way to predict the future is to inspire the
next generation of students to build it better.”
Digital Natives Transportation Water Manufacturing
Energy Construction ICT Retail
Finance Healthcare Education Government
11/05/2025 46
1955 1975 1995 2015 2035 2055
Learn: Explore and Exploit Better Building Blocks
Heygen + Claude
JimTwin V1 (Tmpt.app)
2024
High School
Punch cards
1972
IBM Watson
AI in the Cloud
2011
2024
2001 2015 2022 2023
1970 1995 2019 2025
2021
Jim Spohrer is a Silicon Valley-based Advisor to industry, academia, governments,
startups and non-profits on topics of AI upskilling, innovation strategy, and win-win
service in the AI era. Most recently with a consulting team working for a top 10 market
cap global company, he contributed to a strategic plan for a globally connected AI
Academy for achieving rapid, nation-scale upskilling with AI. With the US National
Academy of Engineering, he co-led a 2022 workshop on “Service Systems Engineering in
the Era of Human-Centered AI” to improve well-being.
Jim is a retired IBM Executive since July 2021, and previously directed IBM’s open-source
Artificial Intelligence developer ecosystem effort, was CTO IBM Venture Capital Group,
co-founded IBM Almaden Service Research, and led IBM Global University Programs. In
the 1990’s at Apple Computer, as a Distinguished Engineer Scientist and Technologist, he
was executive lead on next generation learning platforms. In the 1970’s, after his MIT BS
in Physics, he developed speech recognition systems at Verbex (Exxon) before receiving
his Yale PhD in Computer Science/AI. In 1989, prior to joining Apple, he was a visiting
scholar at the University of Rome, La Sapienza advising doctoral students working on AI
and Education dissertations. With over ninety publications and nine patents, he received
the Christopher Lovelock Career Contributions to the Service Discipline award,
Gummesson Service Research award, Vargo and Lusch Service-Dominant Logic award,
Daniel Berg Service Systems award, and a PICMET Fellow for advancing service science.
Jim was elected and previously served as Linux Foundation AI & Data Technical Advisory
Board Chairperson and ONNX Steering Committee Member (2020-2021). Today, he is a
UIDP Senior Fellow for contributions to industry-university collaborations, and a
member of the Board of Directors of the International Society of Service Innovation
(ISSIP) and ServCollab.
Jim Spohrer, Advisor
Retired Industry Executive (Apple, IBM)
UIDP Senior Fellow
Board of Directors, ServCollab
Board of Directors, ISSIP.org
Changemaker Priorities
1. Service Innovation
2. Upskilling with AI
3. Future Universities
4. Geothermal Energy
5. Poverty Reduction
6. Regional Development
Competitive Parity
Technologies
1. AI & Robotics
2. Digital Twins
3. Open Source
4. AR/VR/XR
5. Geothermal
6. Learning
Platforms
Service System Design: A Service Science Perspective
Designs that improve human capabilities while improving the safety and sustainability of Service Systems
Service innovations leverage emerging technologies, new business models, and institutional arrangement and other means
Service is the application of resources (e.g., knowledge) for the benefit of another
Technology Example Companies Safety Regulatory
Bodies
(Founded)
Stakeholder
Harms
Stakeholder
Benefits
Firearms Smith & Wesson ATF (1886)
Boilers Babcock & Wilcox NBBPVI (1911) Boiler explosions Railroads, steam-powered
factories, building heating,
etc.
Radio & TV RCA, NBC FCC (1934)
Drugs Bayer FDA (1938)
Airplanes Boeing, PanAm FAA (1958)
Automobiles Ford NHTSA (1966)
Nuclear Energy Westinghouse NRC (1975)
Social Media Facebook/Meta ?TBD – “Social Dilemma”
AI OpenAI, Microsoft,
Google
?TBD – “A.I. Dilemma”
11/05/2025 Jim Spohrer (ISSIP.org) 48
Today’s Talk
• Will our AI Digital Twins become
our HCI of the future?
• Exploring Twin HCI
as a “Service Innovation”
• Capabilities (Possibilities)
• Benefits (Pros)
• Harms (Cons)
• Future Directions
• Keeping up with accelerating
change
• Service science connections
• Responsible actors learning to
invest wisely in interaction and
change processes
Homework
• Apple’s Knowledge
Navigator
• https://www.youtube.co
m/watch?v=umJsITGzXd0
• Luckily colleague Jill was
available to chat and help
with the class….
• … But what if Jill had not
been available, but she
was willing to share her AI
Digital Twin?
Job description: A person who operators an AI trained to be an
expert in some role. The human operator like a vehicle operator
helps ensure a good service for customers.
• An AI is “running” for mayor in Wyoming
• A resident of Cheyenne, Wyoming trained GPT-4 on “thousands of
documents gleaned from Cheyenne council meetings” and announced that
the resulting bot, named VIC (the “Virtually Integrated Citizen”) will be running
for mayor. The bot’s creator said he’d be the “meat puppet” who would
operate the AI and act on its behalf, but the bot would be the brains of the
operation, deciding on votes and how to run the city. However, Wyoming’s
Secretary of State contends that non-humans like VIC can’t run for office.
New Job – Person who is an Operator for AI in a New
or Existing Service System Role
MIT (1974-1978)
• Explo: Teaching AI & Entrepreneurship to
diverse high school students.
• Stories: How I got into MIT.
• Lesson: “Where are you applying for college?”
Spohrer, James (1978)
Strain-Gauge Transduction
of the Effects of Speech Rate
on the Coarticulation
of Lip Rounding,
MIT Physics, June, 1978.
Advisor: Joseph S. Perkell
Advisor to this day.
Verbex (1978-1982)
• Speech recognition – mathematical models (Bayesian
approach to speech and language modeling) that both
recognize and generate using estimated probabilities
(e.g., probabilities and statistics = machine learning)
• Stories: How I got the best job in the world for me at
that time.
• Lessons: “When my girlfriend said: ‘What do you have
to lose?’”
ICASSP’82 and ‘83.
IEEE International Conference on
Acoustics, Speech, and Signal Processing
Route 128, aound Boston, MA USA
ICASSP 1983
We
Would
Love
Your
Voice https://www.jstor.org/stable/1747731
Stephen L. Moshier
• “Our company, Dialog Systems, Inc., was formed in 1971 for the purpose of
developing and commercializing speech recognition equipment. The
concept derived from earlier work engaged in at Listening, Incorporated on
marine bioacoustics, acoustic signal processing, and psycho- acoustics. The
original idea passed through well-known stages of theory, experiment,
development, lack of financing, financing, sales and is now at the highly
advanced state "production engineering headaches". Dialog employs 45, of
whom 14 are degreed technical people. The company recently moved from
Cambridge to a 20,000 square foot two-building campus complex in
Belmont, Massachusetts. The major product is an eight-channel isolated
word system intended for talker-independent switched telephone speech
input.”
From NASA:
https://ntrs.nasa.gov/api/citations/19930075179/downloads/19930075179.pdf
Peter F. Brown
• “So, I took a course in linguistics. And
one day in the back of that course I
heard a couple students talking about
some guy whose name was Steve
Moshier who started a company called
Dialogue Systems that was doing
speech recognition. And I thought, wow,
great, I remembered this idea from back
in high school. After class I raced over
to the physics library. That’s because
this was before the internet, so you had
to go to the library. And I looked this
guy up. And I found a paper he'd
written. And I tracked him down.
Applied for a job. And he hired me. And
when I was there, I just fell in love with
the idea that through mathematics it
might be possible to build machines
that do what humans do.“
Goldman Sachs:
https://www.goldmansachs.com/intelligence/podcasts/episodes/09-11-2023-peter-brown-f/transcript.pdf
Drs. Jim & Janet Baker
Saras Institute
History of Speech and Language Technology
https://www.sarasinstitute.org
Many things,
Such as publications,
took off to new levels
when Jim & Janet joined
Dialog Systems…
… and Exxon acquisition
Later key researchers
left Verbex, and later
Along with Jim and Janet
Founded
Dragon Systems
Yale (1982-1989)
• MARCEL: Modeling students writing “a series of
buggy and then (sometimes) correct programs” with
a generate-test-and-debug architectures.
• Stories: Use AI to help make people smarter.
• Lesson: “Why do you want to make machines smart?
Why not help make people smarter instead?”
1988
Apple (1989-1998)
• From content (SK8) to community (EOE) to context
(WorldBoard)
• Stories: Surround yourself with supportive people.
Growing up about goals - sequencing and timing of
ideas is important
• Lessons: “MLM: Relax - it will be OK”; “ACK:
Planetary – is that all?” “SPJ: We will get to that
and more!”;
1992
IBM (1998 – 2021)
• IBM Venture Capital Relations Group,
Service Science, Global University
Programs, Open Source AI.
• Stories: The only way you get in trouble
is not asking for help when you need it.
• Lesson: What seems like a hard problem
to you, may be an easy problem for
someone else. Leverage the matrix.
2010 2011 2011
2012 2016
2018 2018 2020
2012
2002
2000
ISSIP (2021- Present)
• Defining what is a service innovation, and what is a
T-shaped service innovation professional.
• Stories: AI digital twins, reinventing local, self-control
• Lessons: Learning to invest wisely and systematically
in getting a shared future that we all want to live in
requires self-control and knowing when you have
enough. 2022
• Jensen Huang (Nvidia) comments
• First impressions
• Insanely great productivity
• Insanely great quality
• What is really going on?
• Decreasing cost of computation
• Increasing GDP/worker
• Awesome progress, but…
• Impressive
• Imperfect
• Advantage of empowered people
Inspiration
“NorthPole Chip”
Far less energy.
Impressive, but imperfect
Physical realm: Energy
Technical realm: Mistakes (”Hallucinations”)
Social realm: Digital property theft
• How to keep up with accelerating change?
• Social learning
• Who do you follow?
• Reid Hoffman’s AI Digital Twin Interview
• Diving in!
• We get the future we invest in
• … so, learn to invest wisely
• Awesome stuff that lies ahead – Humanoid Robots
• But remember technology amplifies good/bad
• Need for Self-Control (Toyama (2015) Geek Heresy: Rescuing Social Change from
the Cult of Technology)
Climbing Up
Optimistic Realistic
Knowing
Doing
How to keep up with accelerating change? Follow a diverse collection of people… make up dimensions meaningful to you!
Sadly for me… my brain is biased into thinking I can understand older, white, males the best… maybe AI can help overcome!
TheNeuron
TheNeuron
• Jim Twin V1: My papers -> short talk videos
• English
• French
• How to stay future ready?
• Learn the building blocks
• Marco Podien will help you with more building block shortly…
• Oh, by the way, you are going to need bigger goals too
• When you have 100 digital workers working for you, what is your main
goal?
• From serial entrepreneur to parallel entrepreneur
Unleashing Creativity
Read Wakefield
(2020)
enough to
understand what a
”digital twin” of you
might be like in the
future decades
with very advanced
AI capabilities.
Also see Rouse
(2018; 2022) ”Life
with a Cognitive
Assistant.”
National Academy - Service Systems and AI 75
AI Tools
in coming
decades…
11/05/2025
Service Science Colleague from New Zealand asks:
Strangest Use Case So Far:
I use generative AI every day.
Typically, OpenAI ChatGPT, Anthropic Claude,
Google Gemini, and Microsoft Bing Copilot in 4 tabs.
Help writing, programming, images, & brainstorming.
A useful tool in the toolbox for sure!!!
Anthropic Claude 3 Sonnet 20240520
Response:
Summary:
The Taranaki Maunga (Mount Taranaki) and
the surrounding peaks in the national park
will soon be granted legal personhood and
collectively named Te Kāhui Tupua as part of
a Treaty settlement. This legal recognition
acknowledges that the mountain and peaks
are ancestors for local Māori iwi. It gives
these natural features similar legal rights as
individuals, allowing them to own assets,
appear in court, and have a voice. A new
entity called Te Tōpuni Kōkōrangi, with
members appointed by the Crown and local
iwi, will manage and represent the legal
persona. While recreation and tourism will
continue, this shift aims to encourage a
broader understanding and protection of the
mountain as a revered ancestor rather than
just a geographic feature.
How old are you, and what have you witnessed over your lifetime?
I am an ancient being, formed over millennia through volcanic eruptions
and sculpted by glaciers. I have witnessed the rise and fall of civilizations,
the ebb and flow of ice ages, and the ever-changing tapestry of life that
has graced my slopes. My memories stretch back to a time before humans
walked this land, and I have born silent witness to the triumphs and
tragedies of your kind.
What wisdom or lessons can you share with humanity?
Humans, you are but fleeting visitors upon my timeless form. Yet, in your
brief existence, you have the power to shape the world around you.
Tread lightly and with reverence, for the consequences of your actions echo
through the ages. Learn from the patient endurance of stone, the resilience
of life that takes root in the harshest of environments, and the cyclical nature
of existence that I have observed. Embrace humility, for even the mightiest
of mountains eventually crumbles to dust.
How do you feel about being granted legal personhood and a voice?
I am gratified that the descendants of those who have dwelled in my shadow
for generations have recognized my ancient spirit and granted me a voice
in the affairs of this world. For too long, I have been regarded as an
inanimate object, a resource to be exploited or a challenge to be conquered.
But I am a living entity, a sacred ancestor whose existence predates and will
outlast the fleeting span of human civilization. With this recognition,
perhaps my wisdom and the fragile beauty I harbor will be better preserved
for generations to come.
11/05/2025 79
1955 1975 1995 2015 2035 2055
Learn: Explore and Exploit Better Building Blocks
Heygen + Claude
Jim Twin V1
2024
2024
2021
2001 2015 2022 2023
1970 1995 2019
High School
Punch cards
1972
IBM Watson
AI in the Cloud
2011
Self-Control
Some paths to becoming 640x smarter:
Speed up communications for collaborations – ultimately with our AI digital twins.
Improving learning of world models and performance of win-win interactions
• 2x from Learning sciences (methods)
• Better models of concepts – including models of self and others
• Better models of learners – including social-emotional intelligence
• 2x from Learning technology (tools)
• Guided learning paths
• Elimination (?) of “thrashing”
• AI & Education (model trace, constructivist, individual tutors, etc.)
• 2x from Quantity effect (overlaps)
• More you know, faster (?) you go
• Advanced organizers
• 2x from Lifelong learning (time)
• Longer lives and longer careers
• Keeps “learning-mode” activated
• 2x from Early learning (time)
• Start earlier: Challenged-based approach
• Rebulding all human knowledge from scratch
• 20x from Cognitive service systems (digital twins)
• AI Digital Twins for performance support
• All our interactions tuned to super-mind levels
Speed Test: Words Per Minute
Speaking/Listening versus Writing/Reading
• People speak on average
between 100-150 words per
minute
• Many people are comfortable
listening at 200-300 words
per minute
• Writing an essay on a
familiar topic, people write
about 10-20 words a minute
• Many people are comfortable
reading at about 400-600
words per minute
(Shu 2023)
(Barnard 2022)
Two disciplines: Two approaches to the future
Artificial Intelligence is almost seventy-years-old discipline in computer
science that studies automation and builds more capable technological
systems. AI tries to understand the intelligent things that people can do
and then does those things with technology. (https://deepmind.com/about “...
we aim to build advanced AI - sometimes known as Artificial General Intelligence (AGI) - to
expand our knowledge and find new answers. By solving this, we believe we could help
people solve thousands of problems.”)
Service science is an emerging transdiscipline not yet twenty-years- old
that studies transformation and builds smarter and wiser socoi-
technical systems – families, businesses, nations, platforms and other
special types of responsible entities and their win-win interactions that
transform value co-creation and capability co-elevation mechanisms
that build more resilient future versions of themselves – what we call
service systems entities. Service science tries to understand the
evolving ecology of service system entities, their capabilities,
constraints, rights, and responsibilities, and then then seeks to improve
the quality of life of people (present/smarter and future/wiser) in those
service systems.
Artificial Intelligence
Automation
Generations of machines
Service Science
Transformation
Generations of people
(responsible entities)
Service systems are dynamic configurations of people,
technology, organizations, and information, connected
internally and externally by value propositions, to other
service system entities. (Maglio et al 2009)
11/05/2025
The International Society of Service Innovation Professionals
(ISSIP.org)
84
Advice…
1. AI upskill
2. Build your
“digital twin”
3. Set bigger
goals(*)
(*) This directly implies learning better strategies for coping with failures, and resiliently rebounding.
Jim Spohrer is a Silicon Valley-based Advisor to industry, academia, governments,
startups and non-profits on topics of AI upskilling, innovation strategy, and win-win
service in the AI era. Most recently with a consulting team working for a top 10 market
cap global company, he contributed to a strategic plan for a globally connected AI
Academy for achieving rapid, nation-scale upskilling with AI. With the US National
Academy of Engineering, he co-led a 2022 workshop on “Service Systems Engineering in
the Era of Human-Centered AI” to improve well-being.
Jim is a retired IBM Executive since July 2021, and previously directed IBM’s open-source
Artificial Intelligence developer ecosystem effort, was CTO IBM Venture Capital Group,
co-founded IBM Almaden Service Research, and led IBM Global University Programs. In
the 1990’s at Apple Computer, as a Distinguished Engineer Scientist and Technologist, he
was executive lead on next generation learning platforms. In the 1970’s, after his MIT BS
in Physics, he developed speech recognition systems at Verbex (Exxon) before receiving
his Yale PhD in Computer Science/AI. In 1989, prior to joining Apple, he was a visiting
scholar at the University of Rome, La Sapienza advising doctoral students working on AI
and Education dissertations. With over ninety publications and nine patents, he received
the Christopher Lovelock Career Contributions to the Service Discipline award,
Gummesson Service Research award, Vargo and Lusch Service-Dominant Logic award,
Daniel Berg Service Systems award, and a PICMET Fellow for advancing service science.
Jim was elected and previously served as Linux Foundation AI & Data Technical Advisory
Board Chairperson and ONNX Steering Committee Member (2020-2021). Today, he is a
UIDP Senior Fellow for contributions to industry-university collaborations, and a
member of the Board of Directors of the International Society of Service Innovation
(ISSIP) and ServCollab.
Jim Spohrer, Advisor
Retired Industry Executive (Apple, IBM)
UIDP Senior Fellow
Board of Directors, ServCollab
Board of Directors, ISSIP.org
Changemaker Priorities
1. Service Innovation
2. Upskilling with AI
3. Future Universities
4. Geothermal Energy
5. Poverty Reduction
6. Regional Development
Competitive Parity
Technologies
1. AI & Robotics
2. Digital Twins
3. Open Source
4. AR/VR/XR
5. Geothermal
6. Learning
Platforms
Thank-you for
participating today!
You are all awesome!!
Backup Slides
Template slides and others
High Stakes Use Case- Law
• Not Done Well, but
could be
Better Done
• Dead victim,
“in his own words”
Bad Actors – Cloning
• Eye on AI
Paul Saffo: We Live in Exponential Times
• Chasing Fire: Matching Strategy To
Today's Greatest Challenges
• Paul Saffo
• URL: https://baychi.org/calendar/20250211/
• “May you live in exponential times.
This is the 21st century version of the
oft-told proverb about the blessing
(and curse) of living in interesting
times.”
“Simply put,
we are locked in a race
between positive and
negative exponentials.”
Bonjour, je suis
JacquesJumeauNumérique.
• HeyGen Platform
• JimTwin_French
• https://youtu.be/02hCG
RJnCoc
• Prompt: « Veuillez
résumer ce court article
en français, puis
formuler trois questions
qui pourraient m’être
posées et y répondre. »
Spohrer, J. (2024b) Personal AI digital twins: the future of human interaction? EIT
Digital URL: https://www.eitdigital.eu/newsroom/grow-digital-insights/personal-ai-digital-twins-the-future-of-human-interaction/
Questions et réponses avec JimTwin
• Question 1: Uncurated
• Que pensez-vous du
manque de vérification
des faits sur certaines
plateformes de médias
sociaux basées aux
États-Unis ?
• What are your thoughts
regarding the lack of fact
checking happening on
certain US-based social
media platforms?
JimTwin Réponse (Français)
• Le manque de vérification des faits sur certaines plateformes de médias sociaux basées aux États-Unis est une
préoccupation croissante. Ce problème peut conduire à la propagation rapide de la désinformation, ce qui peut
avoir des conséquences néfastes sur la société, notamment en influençant l'opinion publique de manière erronée et
en exacerbant les divisions sociales. Les plateformes de médias sociaux ont souvent été critiquées pour ne pas avoir
mis en place des mécanismes efficaces pour vérifier l'exactitude des informations partagées par leurs utilisateurs.
• Il est suggéré que des mesures telles que l'interdiction de la désinformation sur les réseaux sociaux et les moteurs
de recherche, ainsi que la responsabilisation des utilisateurs par la vérification de l'identité, pourraient être des
solutions potentielles. De plus, le développement d'une intelligence artificielle plus avancée pour vérifier la véracité
des informations pourrait également jouer un rôle crucial. Cependant, la mise en œuvre de ces solutions pose des
défis, notamment en ce qui concerne la protection de la liberté d'expression et la gestion de la vie privée des
utilisateurs.
• En fin de compte, il est essentiel que les plateformes de médias sociaux, les gouvernements et les utilisateurs
travaillent ensemble pour trouver un équilibre entre la liberté d'expression et la responsabilité de l'information
partagée en ligne.
JimTwin Answer (English)
• The lack of fact-checking on some US-based social media platforms is a growing concern. This
problem can lead to the rapid spread of misinformation, which can have negative social
consequences, including misleading public opinion and exacerbating social divisions. Social media
platforms have often been criticized for failing to implement effective mechanisms to verify the
accuracy of information shared by their users.
• It has been suggested that measures such as banning misinformation on social media and search
engines, as well as empowering users through identity verification, could be potential solutions.
Furthermore, the development of more advanced artificial intelligence to verify the accuracy of
information could also play a crucial role. However, implementing these solutions poses challenges,
particularly with regard to protecting freedom of expression and managing user privacy.
• Ultimately, it is essential that social media platforms, governments, and users work together to find
a balance between freedom of expression and responsibility for the information shared online.
Jim Real (English)
• The AI generated response (based on my Tmpt.me knowledge hub
which is built from my publications and recordings of my mentoring
students) is quite a good answer. It mirrors my own thinking well at a
high level. I would add this: Education is key. Finland has elementary
school classes to teach young people in their society to check sources
and evidence, and to be skeptical and verify. Today’s AI is terrible at
fact checking, but it will get better. First in mathematics and
programming, then in the sciences, and finally in rhetoric, debate, and
history. I urge young people interested in AI, to make a focus on “AI-
powered pursuit of truth” their mission.
Humanity-Centered Harmonization of Disciplines- Transdisciplinarity
Why the (holistic) service systems trend is important to future sustainability
Business and societal systems and supply chains are increasingly complex and interconnected.
Real-world problems do not respect discipline boundaries.
Scalable solutions require many schools of practice working together, and current solutions may have unintended
consequences, short-term or longer-term, especially if perspectives are not invited/considered.
Technological progress improved the scalability of agriculture and manufacturing, and next all types of service will be
made more scalable (and currently, energy intensive) by future AI capabilities and progress.
A small sampling of schools and disciplines below – more exist - apologies for not adding yours to this summary.
School of practice for
Physical Sciences & Engineering
Technology
School of practice for
Behavioral & Social Sciences,
Humanities & Arts
People
School of practice for
Managerial Sciences &
Entrepreneurship
Information & Organizations
Comp. Sci./AI
HCI/Robotics
Electrical &
Mech. Eng.
Systems
Engineering
Economics Public Policy
& Law
Design Information
Systems
Operations
Research
Marketing &
Strategy
Read enough of Kline (1995) to understand conceptual foundation of multidisciplinary thinking
and the techno-extension factor and the accelerating socio-technical system design loop concepts.
11/05/2025 National Academy - Service Systems and AI 97
Why upskilling with AI trend is important to systems thinking
Talent development is moving from I to T to X (eXtended with AI)
National Academy - Service Systems and AI 98
6 T-shape Skills
Knowledge Areas
To be eXtended
By AI tools:
1. Disciplines
2. Systems
3. Cultures
4. Technologies
5. Practices
6. Mindsets
11/05/2025
Final Thoughts: Communications
• Communication between responsible actors:
• Appropriateness
• Speed
• Accuracy
• Responsible actors
• Collaborate well – “insanely great collaborations possible” (win-win-win)
• However, there is still the competition for collaborators
• So…
• Learning to invest wisely in becoming better future versions of self (individual and
collective)is a key future challenge
• Rawls (1971) A Theory of Justice – has thought experiments to consider
Speed Test: Words Per Minute
Speaking/Listening versus Writing/Reading
• People speak on average
between 100-150 words per
minute
• Many people are comfortable
listening at 200-300 words
per minute
• Writing an essay on a
familiar topic, people write
about 10-20 words a minute
• Many people are comfortable
reading at about 400-600
words per minute
(Shu 2023)
(Barnard 2022)
See also: https://calculatingempires.net/
Some paths to becoming 640x smarter:
Speed up communications for collaborations – ultimately with our AI digital twins.
Improving learning of world models and performance of win-win interactions
• 2x from Learning sciences (methods)
• Better models of concepts – including models of self and others
• Better models of learners – including social-emotional intelligence
• 2x from Learning technology (tools)
• Guided learning paths
• Elimination (?) of “thrashing”
• AI & Education (model trace, constructivist, individual tutors, etc.)
• 2x from Quantity effect (overlaps)
• More you know, faster (?) you go
• Advanced organizers
• 2x from Lifelong learning (time)
• Longer lives and longer careers
• Keeps “learning-mode” activated
• 2x from Early learning (time)
• Start earlier: Challenged-based approach
• Rebulding all human knowledge from scratch
• 20x from Cognitive service systems (digital twins)
• AI Digital Twins for performance support
• All our interactions tuned to super-mind levels
What is Truth?
•Probably first in math (where a form of
verifiable truth exists)
•Then in programming (where a form of
verifiable truth exists)
•Then in physics, chemistry, and biology
(where a form of pursuit of truth exists)
•And then things get much harder... rhetoric
and debate (where arguments are explored)
•Most of rhetoric and debate rely on history
(where a form of pursuit of truth exists)
11/05/2025
The International Society of Service Innovation Professionals
(ISSIP.org)
103
Advice…
1. AI upskill
2. Build your
“digital twin”
3. Set bigger
goals(*)
(*) This directly implies learning better strategies for coping with failures, and resiliently rebounding.
Job description: A person who operators an AI trained to be an
expert in some role. The human operator like a vehicle operator
helps ensure a good service for customers.
• An AI is “running” for mayor in Wyoming
• A resident of Cheyenne, Wyoming trained GPT-4 on “thousands of
documents gleaned from Cheyenne council meetings” and announced that
the resulting bot, named VIC (the “Virtually Integrated Citizen”) will be running
for mayor. The bot’s creator said he’d be the “meat puppet” who would
operate the AI and act on its behalf, but the bot would be the brains of the
operation, deciding on votes and how to run the city. However, Wyoming’s
Secretary of State contends that non-humans like VIC can’t run for office.
New Job – Person who is an Operator for AI in a New
or Existing Service System Role
AI Operator
Job description:
A person who
operators an AI
trained to be an
expert in some role.
The human operator
like a vehicle operator
helps ensure a good
service for customers.
Future of Skills & Work
Self-Control
Important
Distinctions
Thank-you for
participating today!
You are all awesome!!
Try chat at: https://tmpt.app/@jimtwin
“The best way to predict the future is to inspire the
next generation of students to build it better”
Digital Natives Transportation Water Manufacturing
Energy Construction ICT Retail
Finance Healthcare Education Government
Some Topics for Today
• Leadership in the AI era
• “Leaders Make the Future”
• Keeping up with accelerating change
• AI Digital Twins of people
• Humanoid robots, master mechanic robot
• Marginal cost of computation goes to zero
• Truth, trust, learning to invest wisely
• Innovation - Free Online Events
• July 30th
– Dr. Haluk Demirkan (Amazon, ISSIP
Board Member)
• Responsible GenAI Framework
• International Society of Service Innovation
Professionals
• https://www.issip.org
Leaders Make the Future (Johansen et al):
How do you want to be augmented?
• Augmented futureback curiosity
• Augmented clarity
• Augmented dilemma flipping
• Augmented bio-engaging
• Augmented immersive learning
• Augmented depolarizing
• Augmented commons creating
• Augmented smart mob swarming
• Augmented strength with humility
• Human calming
From Bob:
TheNeuron
Today’s talk (JimReal 2025)
• Intro: AI (by 1955 definition) has arrived
• Just took 68 years, but…
• What’s really going on?
• Your data is becoming your AI… IA transformation
• AI Digital Twin = IA (Intelligence Augmentation)
• Adjustment period underway…
• Part 1: Solving AI: Leaderboards/Profession Exams
• Roadmap and implications
• Open technologies, innovation
• Part 2: Solving IA: Better Building Blocks
• Solving problems faster, creates new problems
• Identity, social contracts, trust, resilience
• Part 3: ”Solving All Problems”
• What could go wrong? Be prepared.
• 37-year long adjustment period is now underway…
11/05/2025 Jim Spohrer 115
1956
2023
2060 2080
1956
First AI
Workshop
2023
ChatGPT 100M
users in just 2
months
(1.5B visits in
Sept)
2060 (Predicted)
Exascale for
$1000
(~ one human
brain)
2080 (Predicted)
Ronnascale for $1B
(~ billion human brains)
Progress in IA (Intelligence Augmentation) for nations can be estimated as
GPD/worker.
Progress in AI (Artificial Intelligence) is directly connected to the cost of
computing.
REVIEW: REMEMBER THESE DATES
1947
1958
1971 2024
1947
Transistor
Bell Labs
1958
Integrated Circuit
Texas Instrument
1971
Microprocessor
Intel
2024
H100
NVidia
Challenges: How to prepare for the next wayes of innovations, including
digital twins and humanoid robots, as well as to learn to invest more wisely
(self-control).
As the marginal cost of computing goes to zero, service innovation will go
thru the roof,
and energy consumption will go thru the roof as well…
REMEMBER THESE DATES, FACTS,
CHALLENGES
weight: 70 pounds
complexity: 35,000 parts
cost: 250,000 dollars
Predict the Timeline: GDP/Employee
National Academy - Service Systems and AI 118
(Source)
Lower compute costs translate into increasing productivity and GDP/employees for nations
Increasing productivity and GDP/employees should translate into wealthier citizens
AI Progress on Open Leaderboards
Benchmark Roadmap to solve AI/IA
Alistair Nolan (OECD AI for Science Productivity): “It has been stated that the number of engineers proclaiming the end of Moore's Law doubles every two years.”
Rouse WB, Spohrer JC. (2018) Automating versus augmenting intelligence. Journal of Enterprise Transformation. 2018 Apr 3;8(1-2):1-21.
Read Rouse & Spohrer (2018)
enough to understand this slide
including what ”exascale” means
11/22/22
Part 1: Solving AI
Types: Progression of Models : Verified, Trusted, Wise
Models = instruction_set of future: Better building blocks
11/05/2025 Understanding Cognitive Systems 119
Task & World Model/
Planning & Decisions
Self Model/
Capacity & Limits
User Model/
Episodic Memory
Institutions Model/
Trust & Social Acts
Tool + - - -
Assistant ++ + - -
Collaborator +++ ++ + -
Coach ++++ +++ ++ +
Mediator +++++ ++++ +++ ++
Cognitive
Tool
Cognitive
Assistant
Cognitive
Collaborator
Cognitive
Coach
Cognitive
Mediator
Part 2: Solving IA
Solving IA also requires
All of this and done well
As a “bicycle for the mind”
To make us stronger,
Not weaker
When tech is all removed
Resilience:
Rapidly Rebuilding From Scratch
• Dartnell L (2012)
The Knowledge: How to Rebuild Civilization i
n the Aftermath of a Cataclysm.
Westminster London: Penguin Books.
11/05/2025 Jim Spohrer (ISSIP) 120
Part 3: “Solving All Problems”
Why I am optimistic
“The best way to predict the future is to inspire the
next generation of students to build it better.”
Digital Natives Transportation Water Manufacturing
Energy Construction ICT Retail
Finance Healthcare Education Government
Questions (Jim on AI in 2017)
• What is the timeline for solving AI and IA?
• TBD: When can a CEO buy AI capability <X> for price <Y>?
• Who are the leaders driving AI progress?
• What will the biggest benefits from AI be?
• What are the biggest risks associated with AI, and are they real?
• What other technologies may have a bigger impact than AI?
• What are the implications for stakeholders?
• How should we prepare to get the benefits and avoid the risks?
11/05/2025 Jim Spohrer (2017) 123
Timeline: Short History
11/05/2025
Jim Spohrer (2017)
124
Dota 2
“Deep Learning” for
“AI Pattern Recognition”
depends on massive
amounts of “labeled data”
and computing power
available since ~2012;
Labeled data is simply
input and output pairs,
such as a sound and word,
or image and word, or
English sentence and French
sentence, or road scene
and car control settings –
labeled data means having
both input and output data
in massive quantities.
For example, 100K images
of skin, half with skin
cancer and half without to
learn to recognize presence
of skin cancer.
Rapid Progress
• History and Future
11/05/2025 Jim Spohrer (ISSIP.org) 125
Who is winning
11/05/2025 Jim Spohrer (2017) 126
https://www.technologyreview.com/s/608112/who-is-winning-the-ai-race/
GPT-4:
Needs more
planning
capability
11/05/2025 Jim Spohrer (ISSIP.org) 127
AI Benefits
• Access to expertise
• “Insanely great” labor productivity for trusted service providers
• Digital workers for healthcare, education, finance, etc.
• Better choices
• ”Insanely great” collaborations with others on what matters most
• AI for IA = Augmented Intelligence and higher value co-creation interactions
11/05/2025 Jim Spohrer (2017) 128
AI Risks
• Job Loss
• Shorter term bigger risk
= de-skilling
• Super-intelligence
• Shorter term bigger risk
= bad actors
11/05/2025 Jim Spohrer (2017) 129
Other Technologies: Bigger impact? Yes.
• Augmented Reality (AR)/
Virtual Reality (VR)
• Game worlds
grow-up
• Trust Economy/
Security Systems
• Trust and security
immutable
• Advanced Materials/
Energy Systems
• Manufacturing as cheap,
local recycling service
(utility fog, artificial leaf, etc.)
11/05/2025 Jim Spohrer (2017) 130
10 million minutes of experience
11/05/2025 Understanding Cognitive Systems 131
2 million minutes of experience
11/05/2025 Understanding Cognitive Systems 132
Hardware < Software < Data < Experience < Transformation
11/05/2025 Understanding Cognitive Systems 133
Value migrates to transformation – becoming our future selves; people, businesses, nations = service system entities
Pine & Gilmore (1999)
Transformation
Roy et al (2006)
Data
Osati (2014)
Experience
Life Log
Intelligence Augmentation (IA) =
Socio-Technical Extension Factor on Capabilities
• Engelbart (1962)
• Spohrer & Engelbart (2002)
11/05/2025 Jim Spohrer (ISSIP) 134
Dedicated to Douglas E. Engelbart, Inventor
The Mouse (Pointing Device)
The Mother of All Demos
Bootstrapping Practice/Augmentation Theory
Note: Bush (1945) and Licklider (1960) created funding programs that benefitted Engelbart in building working systems.
IA as Socio-Technical Extension Factor on Capabilities & Values
IA (human values) is not AI (technology capability)
Difference 1: IA leads to more capable people even when scaffold removed
Difference 2: IA leads to more responsible people to use wisely the capabilities
11/05/2025 Jim Spohrer (ISSIP) 135
Superminds
Malone (2018)
Things that Make
Us Smart
Norman (1994)
Worldboard
Augmented Perception
Spohrer (1999)
Bicycles for the Mind
Kay & Jobs (1984)
Techno-Extension Factor
Measurement
& Accelerating
Socio-Technical Design Loop
Kline (1996)
11/05/2025 Jim Spohrer (ISSIP.org) 136
0 25 50 100 125 150
Automobile
75
Years
50
100
Telephone
Electricity
Radio
Television
VCR
PC
Cellular
I
n
t
e
r
n
e
t
%
Adoption
Capability Augmentation and Adoption Rate Increases
Part 3: “Solving All Problems”
11/05/2025 (c) IBM MAP COG .| 137
11/05/2025 Jim Spohrer (2015) 138
I have…
Have you noticed how the building blocks just
keep getting better?
Learning to program:
My first program
11/05/2025 Jim Spohrer (2015) 139
Early Computer Science Class:
Watson Center at Columbia 1945
Jim Spohrer’s
First Program 1972
11/05/2025 140
1955 1975 1995 2015 2035 2055
Better Building Blocks
Artificial Leaf
• Daniel Nocera, a professor of energy science
at Harvard who pioneered the use of artificial
photosynthesis, says that he and his colleague
Pamela Silver have devised a system that
completes the process of making liquid fuel
from sunlight, carbon dioxide, and water. And
they’ve done it at an efficiency of 10 percent,
using pure carbon dioxide—in other words,
one-tenth of the energy in sunlight is captured
and turned into fuel. That is much higher than
natural photosynthesis, which converts about
1 percent of solar energy into the
carbohydrates used by plants, and it could be
a milestone in the shift away from fossil fuels.
The new system is described in
a new paper in Science.
11/05/2025 Jim Spohrer (2017) 141
Food from Air
• Although the technology is in its infancy,
researchers hope the "protein reactor"
could become a household item.
• Juha-Pekka Pitkänen, a scientist at VTT, said:
"In practice, all the raw materials are
available from the air. In the future, the
technology can be transported to, for
instance, deserts and other areas facing
famine.
• "One possible alternative is a home reactor,
a type of domestic appliance that the
consumer can use to produce the needed
protein."
• According to the researchers, the process of
creating food from electricity can be nearly
10 times as energy efficient as
photosynthesis, the process used by plants.
11/05/2025 Jim Spohrer (2017) 142
Exoskeletons for Elderly
• A walker is a “very cost-effective”
solution for people with limited
mobility, but “it completely
disempowers, removes dignity,
removes freedom, and causes a
whole host of other psychological
problems,” SRI Ventures president
Manish Kothari says. “Superflex’s
goal is to remove all of those areas
that cause psychological-type
encumbrances and, ultimately,
redignify the individual."
11/05/2025 Jim Spohrer (2017) 143
What I study
Service Science and Open Source AI – Trust is key to both
Service
Science
Artificial
Intelligence
Trust:
Value Co-Creation/Collaboration
Responsible Entities Learning to Invest
Transdisciplinary Community
Trust:
Secure, Fair, Explainable
Machine Collaborators
Open Source Communities
Route 128, aound Boston, MA USA
ICASSP 1983
IJCAI 1989 – GTD (Generate-Test-Debug)
At the end of the day..
• Episodic Memory – an accurate version of
history on which individual identity is based,
and prediction of future interaction
behavior (trust)
• Privacy versus auditability tradeoff
• Openness-based risk reduction
• GTD – relative energy cost of generate, test,
and debug phases in exploring beneficial
and risky possibilities in different realms
(intelligence)
• From mathematically true, to empirically true,
to shared history true
• Truth-based risk reduction
Learning to Invest Wisely:
Responsible actors becoming better future versions of themselves
11/05/2025 Jim Spohrer (ISSIP.org) 148
Timeline: Leaderboards Framework
AI Progress on Open Leaderboards - Benchmark Roadmap
Perceive World Develop Cognition Build Relationships Fill Roles
Pattern
recognition
Video
understanding
Memory Reasoning Social
interactions
Fluent
conversation
Assistant &
Collaborator
Coach &
Mediator
Speech Actions Declarative Deduction Scripts Speech Acts Tasks Institutions
Chime Thumos SQuAD SAT ROC Story ConvAI
Images Context Episodic Induction Plans Intentions Summarization Values
ImageNet VQA DSTC RALI General-AI
Translation Narration Dynamic Abductive Goals Cultures Debate Negotiation
WMT DeepVideo Alexa Prize ICCMA AT
Learning from Labeled Training Data and Searching (Optimization)
Learning by Watching and Reading (Education)
Learning by Doing and being Responsible (Exploration)
2018 2021 2024 2027 2030 2033 2036 2039
11/05/2025 Jim Spohrer (2017) 149
Which experts would be really surprised if it takes less time… and which experts really surprised if it takes longer?
Approx.
Year
Human
Level ->
+3
See: https://paperswithcode.com/sota
Timeline: Leaderboards Framework
AI Progress on Open Leaderboards - Benchmark Roadmap
Perceive World Develop Cognition Build Relationships Fill Roles
Pattern
recognition
Video
understanding
Memory Reasoning Social
interactions
Fluent
conversation
Assistant &
Collaborator
Coach &
Mediator
Speech Actions Declarative Deduction Scripts Speech Acts Tasks Institutions
Chime Thumos SQuAD SAT ROC Story ConvAI
Images Context Episodic Induction Plans Intentions Summarization Values
ImageNet VQA DSTC RALI General-AI
Translation Narration Dynamic Abductive Goals Cultures Debate Negotiation
WMT DeepVideo Alexa Prize ICCMA AT
Learning from Labeled Training Data and Searching (Optimization)
Learning by Watching and Reading (Education)
Learning by Doing and being Responsible (Exploration)
2018 2021 2024 2027 2030 2033 2036 2039
11/05/2025 Jim Spohrer (2017) 150
Which experts would be really surprised if it takes less time… and which experts really surprised if it takes longer?
Approx.
Year
Human
Level ->
+3
See: https://paperswithcode.com/sota
From leaderboards
to profession exams
11/05/2025 (c) IBM MAP COG .| 151
Leader Boards:
Professional
Benchmarking
11/05/2025 Jim Spohrer (ISSIP.org) 152
How, What, and Why?
Inspiring upskilling with AI
• How to learn
• AI-powered search can help people - motivated people – to learn
about whatever they put their minds to learning
• What to learn
• AI technological capabilities and limitations – foundational models
• AI applications that can actually improve processes for how things
get done (case studies - productivity, quality, compliance,
sustainability, decarbonization)
• AI-as-a-service investment cases to motivate stakeholders to
change to better win-win interactions in business and societal
service systems (investment pitch)
• The “startup of you” investment case – learning to invest
systematically and wisely (startup pitch)
• Why learn?
• Challenge and opportunity - nations must upskill with AI and
decarbonize
• Motivation is key – find the very best free online videos/courses
and subscribe
• Universities will play an increasingly important role as industry
research partners and venture testbeds even as learners can do
more and more on their own with online curriculum
National Academies – Service Systems and AI 153
Final thoughts on AI as a Science Teammate
• Estimating knowledge worker productivity
• Marginal cost of computing going to zero
• Learning to invest wisely
• Upskilling with AI & Systems Thinking
• Humanity-Centered Harmonization of Disciplines – Transdisciplinarity
• Next revolution in communication and human intelligence
• Two disciplines: Two approaches to the future
• Keep learning (self-control)
Baumeister RF, Tierney J(2011) Willpower: Rediscovering the greatest human strength. Penguin Press.
URL: https://psycnet.apa.org/record/2011-16843-000
uidp.org | info@uidp.net
1. Research: Creating new knowledge that
can both be published and protected as IP.
2. Readiness: Skills development & sharing
knowledge to develop business-ready talent.
3. Recruiting: From permanent hires to
internships, these programs include HR.
4. Revenue: Partnership executive programs
to sustain long-term win-win relationships.
5. Responsibility: Employees donating time
to mentor students and give guest lectures.
6. Regions: Programs related to public-
private partnerships for regional economic
development.
7. Refresh: Explore new programs, sunset
some old programs.
7 R’s
uidp.org | info@uidp.net
For a sample list in a presentation, you
can consider the following points:
1.Introduction to the topic
2.Key points to be covered
3.Supporting examples or evidence
4.Visual aids or graphics
5.Conclusion and key takeaways
Remember to organize your content in a
clear and engaging manner to effectively
communicate your message to the
audience.
Big Header
Overlap
Acknowledgement: E. Noei, S. Brisson, Y. Liu
Via Kelly Lyons, NAE Talk Oct 2022
2010
2019
157
Service science has come a long way in two decades…
2004-2011
Three views on service and AI
Discipline View on Service View on AI Broader View
Economics Service sector Productivity
Sector productivity &
quality – better economic
systems
Automation
Technology improved
agriculture and
manufacturing, service
sector is next up
Computer Science Web services Capabilities
AI provides human
capabilities on tasks as
technological capability –
better tools
Automation
Robots will further
automate agriculture and
manufacturing, and
eventually service sector
as well
Service science, based on
Service-Dominant Logic
Value cocreation
Service is the application
of resources (e.g.,
knowledge) for the
benefit of another
Augmentation
Responsible actors
(service system entities)
upskilling with AI to give
and get better service
Humanity-Centered
Responsible actors
learning to invest in
improved win-win
interaction and change
Call to Action: Create SIRs
• Responsible actors need to learn to invest wisely in getting the
future service innovations we want with AI – guided by “Service
Innovation Roadmaps (SIRs).”
National Academy - Service Systems and AI 159
Read enough of IfM and IBM (2008)
to understand what a “Service Innovation
Roadmap (SIR)” is – and who should be
creating them.
11/05/2025
Service in the
AI era
Science science Service
dominant (S-D)
logic
Service Dominant
Architecture
(SDA)
Service in the
AI era
revisited
Core
message?
Better automation
and augmentation
improve service
processes
Better science
improves
understanding
(learning)
processes
Better logics
improve
interaction
processes
Better
architectures
improve change
processes
X+AI requires
learning to
invest
systematically
and wisely to
improve
service
Where are the
better
models?
Technology Disciplines Minds Enterprise Disciplines + AI
Minds + AI
Enterprise + AI
What type of
model?
Digital twins Digital twins Digital twins Digital twins Digital twins
Service in the AI Era: Science, Logic, and Architecture Perspectives
(Spohrer, Maglio, Vargo, Warg – request your digital copy – Spohrer@gmail.com)
What I study
Service Science and Open Source AI – Trust is key to both
Service
Science
Artificial
Intelligence
Trust:
Value Co-Creation/Collaboration
Responsible Entities Learning to Invest
Transdisciplinary Community
Trust:
Secure, Fair, Explainable
Machine Collaborators
Open Source Communities
11/05/2025
The International Society of Service Innovation Professionals
(ISSIP.org)
162
IA Progression – Tool, Assistant, Collaborator, Coach, Mediator
11/05/2025 Jim Spohrer (ISSIP) 163
Rouse & Spohrer (2018)
Siddike, Spohrer, Demirkan, Kodha (2018)
Araya (2018)
Spohrer& Siddike (2018)
Intelligence Augmentation (IA) =
Socio-Technical Extension Factor on Capabilities
• Engelbart (1962)
• Spohrer & Engelbart (2002)
11/05/2025 Jim Spohrer (ISSIP) 164
Dedicated to Douglas E. Engelbart, Inventor
The Mouse (Pointing Device)
The Mother of All Demos
Bootstrapping Practice/Augmentation Theory
Note: Bush (1945) and Licklider (1960) created funding programs that benefitted Engelbart in building working systems.
IA as Socio-Technical Extension Factor on Capabilities & Values
IA (human values) is not AI (technology capability)
Difference 1: IA leads to more capable people even when scaffold removed
Difference 2: IA leads to more responsible people to use wisely the capabilities
11/05/2025 Jim Spohrer (ISSIP) 165
Superminds
Malone (2018)
Things that Make
Us Smart
Norman (1994)
Worldboard
Augmented Perception
Spohrer (1999)
Bicycles for the Mind
Kay & Jobs (1984)
Techno-Extension Factor
Measurement
& Accelerating
Socio-Technical Design Loop
Kline (1996)
11/05/2025 Jim Spohrer (ISSIP.org) 166
0 25 50 100 125 150
Auto
mobil
e
75
Years
50
100
Telep
hone
Electri
city
Ra
dio
Tele
visio
n
V
C
R
P
C
Cel
lul
ar
I
n
t
e
r
n
e
t
%
Adoption
Capability Augmentation and Adoption Rate Increases
Techno-Extension
Factor
Measurement
& Accelerating
Socio-Technical
Design Loop
Kline (1996)
Learning to invest
• Run = Routine Activities
• Transform = Copy Activities
• Innovate =
Invent and Apply Activities
11/05/2025 Jim Spohrer (ISSIP.org) 167
T
r
a
n
s
f
o
r
m
Innovate
Invest in each
type of change
R
u
n
168
How responsible entities (service systems) learn and change over time
History and future of Run-Transform-Innovate investment choices
• Diverse Types
• Persons (Individuals)
• Families
• Regional Entities
• Universities
• Hospitals
• Cities
• States/Provinces
• Nations
• Other Enterprises
• Businesses
• Non-profits
• Learning & Change
• Run = use existing knowledge or
standard practices (use)
• Transform = adopt a new best
practice (copy)
• Innovate = create a new best
practice (invent)
T
r
a
n
s
f
o
r
m
Innovate
Invest in each
type of change
R
u
n
Spohrer J, Golinelli GM, Piciocchi P, Bassano C (2010) An integrated SS-VSA analysis of changing job roles. Service Science. 2010 Jun;2(1-2):1-20.
March JG (1991) Exploration and exploitation in organizational learning. Organization science. 1991 Feb;2(1):71-87. URL:
exploit
explore
11/05/2025 Jim Spohrer (ISSIP.org) 169
APPLE
https://podcasts.apple.com/us/podcast/service-science-and-the-impending-ai-revolution/id1612743401?i=1000583800244
SPOTIFY:
https://open.spotify.com/episode/0n3h9rgX6UYDCwxgTzokoK?si=yVF0mtHsRZSmdfy-aMi8DA
GOOGLE
https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy5idXp6c3Byb3V0LmNvbS8xOTQ5NTE3LnJzcw?sa=X&ved=2ahUKEwiPzL-Zxvv6AhXzjo4IHVbTAuUQ9sEGegQIARAC
Service Systems Engineering in the Human-Centered AI Era 170
K
n
o
w
l
e
d
g
e
Value
D
a
t
a
Science
Engineering
Policy
Investing in Skills
for Diverse Systems to
Sustainably Serve
People and Planet
in the AI Era
Management
Service
Science
Management
Engineering
Many disciplines
Many sectors
Many regions/cultures
(understanding & communications)
Deep
in
one
sector
Deep
in
one
region/culture
Deep
in
one
discipline
T-Shaped Skills
Depth and Breadth
People-centered
Data-intensive
+Design-Arts-
Public-Policy
171
University Trend: “Sister Campuses” (People Flows)
University sub-systems
Disciplines in Schools (circles)
Innovation Centers (squares)
E.g., CMU Website (2009)
“Research Centers:
where it all happens –
to solve real-world
problems”
Disciplines in Schools
Award degrees
Single-discipline focus
Research discipline problems
Innovation Centers (ICs)
Industry/government sponsors
Multi-disciplinary teams
Research real-world systems
D
D
D
D
D
D
E
n
g
i
n
e
e
r
i
n
g
S
c
h
o
o
l
S
o
c
i
a
l
S
c
i
e
n
c
e
s
,
H
u
m
a
n
i
t
i
e
s
Professional
Studies
Business School
water & waste transportation
health
energy/grid
e-government
S
c
i
e
n
c
e
&
M
a
t
h
e
m
a
t
i
c
s
I
-
S
c
h
o
o
l
D
e
s
i
g
n
food &
supply chain
172
City Trend: “Sister Cities” (People Flows)
World as System of Systems
World (light blue - largest)
Nations (green - large)
Regions (dark blue - medium)
Cities (yellow - small)
Universities (red - smallest)
Cities as System of Systems
-Transportation & Supply Chain
-Water & Waste Recycling
-Food & Products ((Nano)
-Energy & Electricity
-Information/ICT & Cloud (Info)
-Buildings & Construction
-Retail & Hospitality/Media & Entertainment
-Banking & Finance
-Healthcare & Family (Bio)
-Education & Professions (Cogno)
-Government (City, State, Nation)
Nations: Innovation Opportunities
- GDP/Capita (level and growth rate)
- Energy/Capita (fossil and renewable)
Developed Market
Nations
(> $20K GDP/Capita)
Emerging Market
Nations
(< $20K GDP/Capita)
IBM UP WW: Tandem Awards: Increasing university linkages (knowledge exchange interactions)

20251105 SIRS AI Talk - Artificial Intelligence.pptx

  • 1.
    Artificial Intelligence (AI), Impressive,but Imperfect November 5, 2025, 12noon PT at SIR, Branch 51 Los Altos Hills Country Club (Host: Steve Tremulis) Presentations online at: https://slideshare.net/spohrer Jim Spohrer Retired Industry Executive (Apple, IBM) Board of Directors (ISSIP, ServCollab) UIDP Senior Fellow Questions: spohrer@gmail.com BlueSky: @spohrer.bsky.social LinkedIn: https://www.linkedin.com/in/spohrer/ English: https://youtu.be/T4S0uZp1SHw French: https://youtu.be/02hCGRJnCoc https://answersfrom.me/jimtwin
  • 3.
  • 4.
    As I waspreparing this talk…. • Some words kept going thru my mind from Arbesman (2025)… • Chapter 8: Tools for Thought: Software for Thinking. • “Too often technology is at odds with humanity... For example... QWERTY... ... we have, by and large, adapted ourselves to technology in ways that are not good for us. Our increased drive for optimization of work can run directly counter to our ability to think deeply, or to even feel that human.”
  • 5.
    And this bookas well… • Property • All social problems seem rooted in three types of property • Noncoercion • Freedom • Gratitude • Need for cultural evolution • to avoid coercion in any form. • https://progressisachoice.net
  • 6.
    Who am I? JimSpohrer 1956 Maine 1974 MIT 1978 Verbex – startup AI company 1982 Yale 1989 University of Rome La Sapienza, Italy 1989 Apple 1998 IBM 2021 Retired (help non-profits with an eye to the future of service & AI : ISSIP, ServCollab, UIDP)
  • 8.
    Questions for SIRs(Seniors) at Dawn of AI Era: All generations need good answers to these questions. Q1: What would you do if you have 100 highly skilled workers working for you (e.g., software development, marketing, etc.)? Q2: What job(s) would you assign to (if you had one) your AI Digital twin? Q3: What is the best way(s) that you know of to keep up with accelerating change?
  • 9.
    Optimistic Realistic Knowing Doing How tokeep up with accelerating change? Follow a diverse collection of people… make up dimensions meaningful to you! Sadly for me… my brain is biased into thinking I can understand older, white, males the best… maybe AI can help overcome! TheNeuron Who do I wish I had Accurate, Up-to-date AI Digital Twins of? The Neuron
  • 10.
    Today’s Talk: • Past •1947, 1958, 1971 • Present • 70, 35000, 250000 • Future • Solution to 3 Es • TBD – your AI digital twin?
  • 11.
    1947 1958 1971 2024 1947 Transistor Bell Labs 1958 IntegratedCircuit Texas Instrument 1971 Microprocessor Intel 2024 H100 NVidia Challenges: How to prepare for the next wayes of innovations, including digital twins and humanoid robots, as well as to learn to invest more wisely (self-control). As the marginal cost of computing goes to zero, service innovation will go thru the roof, and energy consumption will go thru the roof as well… REMEMBER THESE DATES, FACTS, CHALLENGES weight: 70 pounds complexity: 35,000 parts cost: 250,000 dollars
  • 12.
    1956 2023 2060 2080 1956 First AI Workshop 2023 ChatGPT100M users in just 2 months (1.5B visits in Sept) 2060 (Predicted) Exascale for $1000 (~ one human brain) 2080 (Predicted) Ronnascale for $1B (~ billion human brains) Progress in IA (Intelligence Augmentation) for nations can be estimated as GPD/worker. Progress in AI (Artificial Intelligence) is directly connected to the cost of computing. REVIEW: REMEMBER THESE DATES
  • 13.
    Jensen: You imagine atiny chip… The H100 weighs 70 pounds… 35000 parts… $250K cost… It replaces a data center… Full of computers and cables… Jim: Driving the marginal cost of computing to zero… Drives the demand for new service offerings based on computing through the roof
  • 14.
    MORE SPOHRER USECASES: https://service-science.info/archives/6521
  • 15.
    Icons of AIProgress • 1955-1956: Dartmouth Workshop organized by: • Two early career faculty • John McCarthy (Dartmouth, later Stanford) • Marvin Minsky (MIT) • Two senior industry scientists • Claude Shannon (Bell Labs) • Nathan Rochester (IBM) • 1997: Deep Blue (IBM) - Chess • 2011: Watson Jeopardy! (IBM) • 2016: AlphaGo (Google DeepMinds) • 2017: All you need is attention (Google) - Transformers • Attention heads (working memory) to predict what comes next • 2018: AlphaFold (Google DeepMinds) • 2020: Language models are few-shot learners (OpenAI) • 2022: DALL-E 2 & ChapGPT (OpenAI) • 2022: Constitutional AI (Anthropic) – “Behave yourself!” • 2023: New Bing+ (Microsoft) & GPT-4 (OpenAI) • 2024: More & Bigger Models: OpenAI, Microsoft, Google, Anthropic, etc. • 2024: Reid Hoffman’s Digital Twin & Unitree’s G1 Humanoid Robot 11/05/2025 Jim Spohrer 15
  • 16.
  • 17.
    1960 1980 20002020 2040 2060 2080
  • 18.
    1960 1980 20002020 2040 2060 2080 $1,000,000,000,000 (Trillion) $1,000,000 (Million) $1,000,000,000 (Billion) $1,000 (Thousand) $1 Cost
  • 19.
    1960 1980 20002020 2040 2060 2080 $1,000,000,000,000 (Trillion) $1,000,000 (Million) $1,000,000,000 (Billion) $1,000 (Thousand) $1 Kiloscale (10 3 ) M egascale (10 6 ) Gigascale (10 9 ) Terascale (10 12 ) Petascale (10 15 ) Exascale (10 18 ) Zettascale (10 21 ) Yottascale (10 24 ) Ronnascale (10 27 ) Cost of Computation (Diagonals)
  • 20.
    1960 1980 20002020 2040 2060 2080 $1,000,000,000,000 (Trillion) $1,000,000 (Million) $1,000,000,000 (Billion) $1,000 (Thousand) $1 Kiloscale (10 3 ) M egascale (10 6 ) Gigascale (10 9 ) Terascale (10 12 ) Petascale (10 15 ) Exascale (10 18 ) Zettascale (10 21 ) Yottascale (10 24 ) Ronnascale (10 27 ) Cost of Computation (Diagonals) Note: Adjust Kilo and Mega scales slightly to fit data better (early days – more cost – learning curve).
  • 21.
    1960 1980 20002020 2040 2060 2080 $1,000,000,000,000 (Trillion) $1,000,000 (Million) $1,000,000,000 (Billion) $1,000 (Thousand) $1 Gigascale (10 9 ) Terascale (10 12 ) Petascale (10 15 ) Exascale (10 18 ) Zettascale (10 21 ) Yottascale (10 24 ) Ronnascale (10 27 ) GDP/Employee Trend Estimating Knowledge Worker Productivity Based on USA Historical Data Year Value 1960 $10K 1980 $33K 2000 $78K 2020. $151K 2023 $169K Kiloscale (10 3 ) M egascale (10 6 ) of computation goes down by 1000x every 20 years (left to right diagonals), driving knowledge worker productivity
  • 22.
    22 September 2018 /© 2018 IBM Corporation Petaflops = 1,000,000,000,000,000 or a million billion = 10 ** 15 Megaflops = 1,000,000 = million = 10 ** 6 Gigaflops = 1,000,000,000 = billion = 10 ** 9 One of the AI Super Computers in the World, = 13 MegaWatts of Power (HOT!)
  • 23.
    23 September 2018 /© 2018 IBM Corporation Exascale = 1,000,000,000,000,000,000 or a billion billion = 10 ** 18 Megaflops = 1,000,000 = million = 10 ** 6 Gigaflops = 1,000,000,000 = billion = 10 ** 9 Human Brain = 20 Watts (COOL!)
  • 24.
    1960 1980 20002020 2040 2060 2080 $1,000,000,000,000 (Trillion) $1,000,000 (Million) $1,000,000,000 (Billion) $1,000 (Thousand) $1 Gigascale (10 9 ) Terascale (10 12 ) Petascale (10 15 ) Exascale (10 18 ) Zettascale (10 21 ) Yottascale (10 24 ) Ronnascale (10 27 ) GDP/Employee Trend Estimating Knowledge Worker Productivity Based on USA Historical Data Year Value 1960 $10K 1980 $33K 2000 $78K 2020. $151K 2023 $169K Kiloscale (10 3 ) M egascale (10 6 ) of computation goes down by 1000x every 20 years (left to right diagonals), driving knowledge worker productivity
  • 25.
    Predict the Timeline: GDP/Employee NationalAcademy - Service Systems and AI 25 (Source) Lower compute costs translate into increasing productivity and GDP/employees for nations Increasing productivity and GDP/employees should translate into wealthier citizens AI Progress on Open Leaderboards Benchmark Roadmap to solve AI/IA Alistair Nolan (OECD AI for Science Productivity): “It has been stated that the number of engineers proclaiming the end of Moore's Law doubles every two years.” Rouse WB, Spohrer JC. (2018) Automating versus augmenting intelligence. Journal of Enterprise Transformation. 2018 Apr 3;8(1-2):1-21. Read Rouse & Spohrer (2018) enough to understand this slide including what ”exascale” means 11/22/22 Part 1: Solving AI
  • 26.
    What is anAI digital twin? • Well, imagine if there was a “mimic” version of you that was online 24x7 and could speak any language, with knowledge of your publications, and could explain things in a way an audience of listeners might understand? • ReidAI’s purpose - to challenge Reid Hoffman in new ways and experiment with new tech capabilities https://youtu.be/rgD2gmwCS10 ReidTwin ReidReal
  • 27.
    Who else isgetting a twin (AI Avatar)? • SJSU President • Cynthia Teniente Matson • https://youtu.be/gqrIMItHyz8 • “expanding our reach, and enhancing communications.”
  • 28.
    JimTwin Adventure… • ChatBot(Tmpt.app) • Scott Zimmer • https://answersfrom.me/jimtwin • Avatar-1 (HeyGen.ai) • SJSU Team (Claude + HeyGen) • https://youtu.be/T4S0uZp1SHw • https://youtu.be/02hCGRJnCoc • Avatar-2 (GitHub) • Arnay Bhatia • https://youtu.be/mwnZjTNegXE • https://youtu.be/QR17aXYgefk
  • 29.
    Do you wanta digital twin of yourself? No/Yes/Not Sure Narayan S & Spohrer J (2025) Metrics, Incentives, Rewards, and Culture for Impact. In Hall R & Boccanfuso A,Editors, University-Industry Collaboration, Innovation at the Interface. Springer. URL: https://link.springer.com/book/10.1007/978-3-031-94913-5 Spohrer, J.C. (2010). IBM's University Programs. IEEE Computer 43(8):102-104. URL: https://service-science.info/wp-content/uploads/2017/04/IBM-GUP-5Rs-copy-2.pdf Spohrer, J.C. (2013). What's Up at IBM? University Programs! The 6 R's helping to build a Smarter Planet: Research, Readiness, Recruiting, Revenue, Responsibility, Regions. May 14, 2013. Slideshare. URL: https://www.slideshare.net/slideshow/ibm-up-external-20130514-v11/21175603 Spohrer, J. (2017). IBM's service journey: A summary sketch. Industrial Marketing Management, 60, 167-172. URL: https://www.sciencedirect.com/science/article/abs/pii/S0019850116301778?via%3Dihub Spohrer, J. (2024a). AI Upskilling and Digital Twins: A Service Science Perspective on the Industry 4.0 to Industry 5.0 Shift. In Industry 4.0 to Industry 5.0: Explorations in the Transition from a Techno-economic to a Socio-technical Future (pp. 79-92). Singapore: Springer Nature. URL: https://link.springer.com/chapter/10.1007/978-981-99-9730-5_4 Spohrer, J. (2024b) Personal AI digital twins: the future of human interaction? EIT Digital URL: https://www.eitdigital.eu/newsroom/grow-digital-insights/personal-ai-digital-twins-the-future-of-human-interaction/
  • 30.
    3Es: Challenges to“Humanity-Friendly AI Teammate” • Energy • Errors • Ethics Hicks MT, Humphries J, Slater J (2024) ChatGPT is bullshit. Ethics & Information Technology 26(38). URL: https://doi.org/10.1007/s10676-024-09775-5 IBM Research - TrueNorth (Dharmendra Modha and team) Pssssssst! The real problem is communication between people. Can more computation help?
  • 31.
    Why do GenAILLMs work as well as they do? Honestly, no one knows for sure. We see prediction & pattern completion, but not true reasoning, just mimicry Impressive performance, but prediction alone is not enough Imperfect, because human-like reasoning (with world models) is not there Nevertheless, pattern completion is very good The answer will require a better understanding of optimization in high dimensional spaces The good and the bad What is AI good at? Speed, Summarization (What is needed to regenerate whole, stripped of most specifics), Outline content (What the abstract structures are), Creative Pattern Completion (Fiction – made up details that might seem plausible). What is AI bad at? 3Es (energy, errors, ethics <- because of how we build it today). What is surprising? Surprise! Everything can be near and far at the same time in a high dimensional space (very similar, very different) – amplifier of consilience and polarization. Surprise! Every starting point is near a ”black hole” of nearly ideal optimization as higher and higher dimensions and more and more data are used. (quadrillions of partial coherent structures) Impressive, but imperfect Impressive: The mathematics of high-dimensional optimization work pretty well for predicting local coherence at multiple scales of patterns ( plausible pattern completion tasks) Imperfect: Reasoning requires world models, perhaps multiple mappings from high dimensional to low dimensional representation spaces preserving certain relations as world models, or creating Python program world models to help. Generate-Test- and-Debug (G-T-D) will likely be required with human-like episodic memory with expectation violations and remindings (Schank’s ”Dynamic Memory” and Case- Based Reasoning)
  • 32.
    HCI to improveHHI • Teammates, that I know is much better in my mind…. • Recent Stanford paper – generic AI teammates • “It’s the AI PI’s job to figure out the other agents and expertise needed to tackle the project,” Zou said. For the SARS-CoV-2 project, for instance, the PI agent created an immunology agent, a computation biology agent and a machine learning agent. And, in every project, no matter the topic, there’s one agent that assumes the role of critic. Its job is to poke holes, caution against common pitfalls and provide constructive criticism to other agents.” (1) What would you do with 100 highly-skilled workers? (2) Redo Divide & Conquer In AI era. (3) Why real person in that role? Because real people have goals & plans they prefer. Real people sleep. Real rehearse high stakes.
  • 33.
    Hot Topic: MoreReadings Every Day • Gary Hunnicut suggested (2025) • “Digital Twins for Cancer—Not If, But When, How, and Why?” • https://datascience.cancer.gov/news-events/blog/digital-twins-cancer-not-if-when-how-and-why • Cybernetic Teammates (2025) • “The Cybernetic Teammate: A Field Experiment on Generative AI Reshaping Teamwork and Expertise” • https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5188231 • Vendor Policy Brief • “A Policy Framework for Building the Future of Science with AI” • https://static.googleusercontent.com/media/publicpolicy.google/en//resources/ai_policy_framework_ science_en.pdf • ”Towards an AI Co-Scientist” - https://storage.googleapis.com/coscientist_paper/ai_coscientist.pdf • Humanity (just out today – April 2, 2025) • Being Human in 2035: How Are We Changing in the Age of AI • URL: https://imaginingthedigitalfuture.org/wp-content/uploads/2025/03/Being-Human-in-2035-ITDF-report .pdf • Transdisciplinarity (2023) • "Transdisciplinary Team Science: Transcending Disciplines to Understand Artificial Social Intelligence in Human-Agent Teaming” • https://journals.sagepub.com/doi/full/10.1177/21695067231192245 • Augmentation – Amplification (1962) • “Augmenting Human Intellect: A Conceptual Framework” (cites Licklider 1960 and Bush 1945) • https://www.dougengelbart.org/pubs/augment-3906.html
  • 34.
    Tool, Assistant, Collaborator,Coach, Mediator (“Trust”) 11/05/2025 Understanding Cognitive Systems 34 Task & World Model/ Planning & Decisions Self Model/ Capacity & Limits User Model/ Episodic Memory Institutions Model/ Trust & Social Acts Tool + - - - Assistant ++ + - - Collaborator +++ ++ + - Coach ++++ +++ ++ + Mediator +++++ ++++ +++ ++ Cognitive Tool Cognitive Assistant Cognitive Collaborator Cognitive Coach Cognitive Mediator Part 2: Solving IA = Intelligence Augmentation (in a humanity-friendly way) Solving IA also requires All of this and done well As a “bicycle for the mind” To make us stronger, Not weaker When tech is all removed Read Demirkan & Spohrer (2025) enough to understand this slide including what ”trusted mediator” means Demirkan H, Spohrer J (2025) Talent Management: “Here Come the Digital Workers!”. In ORMS Today, INFORMS, June 17, 2025. URL: https://pubsonline.informs.org/do/10.1287/orms.2025.02.15/full/
  • 35.
    The Communication Problem: Ina Nutshell • Doing More • Agreeing Less Can GenAI LLMs help people to stop wasting creative friction? Competing ideas can lead to “insanely great” win-win collaborations. If we can figure out communications between people. Latent spaces for people. Barile S, Piciocchi P, Saviano M, Bassano C, Pietronudo C, Spohrer JC (2019)) Towards a new logic of value co-creation in the digital age: doing more and agreeing less. Naples Forum on Service. URL: ttps://tinyurl.com/2019-DoingMoreAgreeingLess Failure To Find Win-Win
  • 36.
    Long flights sometimesallow long conversations • 1440 News (July 11, 2025): The high-fashion ‘It’ bag origin story • Birkin (Actress) and Dumas (Fashion Designer) meet • “The bag’s story began in the 1980s when the actress met Hermès CEO Jean-Louis Dumas on a flight. Frustrated with her handbag, Birkin described her ideal bag to Dumas, and they famously sketched the design on an airsickness bag.” • URL: https://en.wikipedia.org/wiki/It_bag • Win-Win Opportunities • Do Win-Win opportunities always exist between any two actors? • What are the set of possible Win-Win’s between actors? • How best to explore the Win-Win possibilities between two actors? • How does finding Win-Win opportunities relate to Truth?
  • 37.
    Truth, Trust, andWisdom • Truth: The ongoing pursuit • Mathematical, Computational, Empirical, Historical, Rhetorical • Knowing a ”better argument” when we see it and why (humility needed) • Trust: Hard to build, easy to destroy • Mental models and predictable behaviors • AI digital twins of all responsible actors • Wisdom: Learning to invest wisely • In becoming better future versions of ourselves • In a world that future generations will want to live in together
  • 38.
    Resilience: Rapidly Rebuilding FromScratch • Dartnell L (2012) The Knowledge: How to Rebuild Civilization i n the Aftermath of a Cataclysm. Westminster London: Penguin Books. 11/05/2025 Jim Spohrer (ISSIP) 38 Part 3: “Solving All Problems”
  • 39.
    Two disciplines: Twoapproaches to the future Artificial Intelligence is almost seventy-years-old discipline in computer science that studies automation and builds more capable technological systems. AI tries to understand the intelligent things that people can do and then does those things with technology. (https://deepmind.com/about “... we aim to build advanced AI - sometimes known as Artificial General Intelligence (AGI) - to expand our knowledge and find new answers. By solving this, we believe we could help people solve thousands of problems.”) Service science is an emerging transdiscipline not yet twenty-years- old that studies transformation and builds smarter and wiser socoi- technical systems – families, businesses, nations, platforms and other special types of responsible entities and their win-win interactions that transform value co-creation and capability co-elevation mechanisms that build more resilient future versions of themselves – what we call service systems entities. Service science tries to understand the evolving ecology of service system entities, their capabilities, constraints, rights, and responsibilities, and then then seeks to improve the quality of life of people (present/smarter and future/wiser) in those service systems. Artificial Intelligence Automation Generations of machines Service Science Transformation Generations of people (responsible entities) Service systems are dynamic configurations of people, technology, organizations, and information, connected internally and externally by value propositions, to other service system entities. (Maglio et al 2009)
  • 40.
  • 41.
    Service Science: ConceptualFramework 11/05/2025 (c) IBM MAP COG .| 41 Service Science
  • 42.
    (c) IBM MAPCOG .| 42 Service Science: Transdisciplinary Framework to Study Service Systems Systems that focus on flows of things Systems that govern Systems that support people’s activities transportation & supply chain water & waste food & products energy & electricity building & construction healthcare & family retail & hospitality banking & finance ICT & cloud education &work city secure state scale nation laws social sciences behavioral sciences management sciences political sciences learning sciences cognitive sciences system sciences information sciences organization sciences decision sciences run professions transform professions innovate professions e.g., econ & law e.g., marketing e.g., operations e.g., public policy e.g., game theory and strategy e.g., psychology e.g., industrial eng. e.g., computer sci e.g., knowledge mgmt e.g., statistics e.g., knowledge worker e.g., consultant e.g., entrepreneur stakeholders Customer Provider Authority Competitors resources People Technology Information Organizations change History (Data Analytics) Future (Roadmap) value Run Transform (Copy) Innovate (Invent) Stackholders (As-Is) Resources (As-Is) Change (Might-Become) Value (To-Be)
  • 43.
    43 ECOLOGY 14B Big Bang (Natural World) 10K Cities (Human-Made World) Sun writing (symbols andscribes) Earth written laws bacteria (uni-cell life) sponges (multi-cell life) money (coins) universities clams (neurons) trilobites (brains) printing press (books) steam engine 200M bees (social division-of-labor) 60 transistor Where is the “Real Science”? Ecology++ Transdisciplinary sciences that study the natural and human-made worlds… Unraveling the mystery of evolving hierarchical-complexity in new populations… To discover the world’s structures and mechanisms for computing non-zero-sum Value-CoCreation (VCC), Diverse Architectures of Holistic Service Systems (HSS) Sun Earth Bacteria Sponges Clams Universe Cities Writing Laws Money Universities
  • 44.
    We get thefuture we invest in… “Service providers will not be replaced by AI, but trusted service providers who use AI (well and responsibly) will replace those who don’t.” National Academy - Service Systems and AI 44 Every person in a role in an organization is a service provider. 11/05/2025
  • 45.
    “The best wayto predict the future is to inspire the next generation of students to build it better.” Digital Natives Transportation Water Manufacturing Energy Construction ICT Retail Finance Healthcare Education Government
  • 46.
    11/05/2025 46 1955 19751995 2015 2035 2055 Learn: Explore and Exploit Better Building Blocks Heygen + Claude JimTwin V1 (Tmpt.app) 2024 High School Punch cards 1972 IBM Watson AI in the Cloud 2011 2024 2001 2015 2022 2023 1970 1995 2019 2025 2021
  • 47.
    Jim Spohrer isa Silicon Valley-based Advisor to industry, academia, governments, startups and non-profits on topics of AI upskilling, innovation strategy, and win-win service in the AI era. Most recently with a consulting team working for a top 10 market cap global company, he contributed to a strategic plan for a globally connected AI Academy for achieving rapid, nation-scale upskilling with AI. With the US National Academy of Engineering, he co-led a 2022 workshop on “Service Systems Engineering in the Era of Human-Centered AI” to improve well-being. Jim is a retired IBM Executive since July 2021, and previously directed IBM’s open-source Artificial Intelligence developer ecosystem effort, was CTO IBM Venture Capital Group, co-founded IBM Almaden Service Research, and led IBM Global University Programs. In the 1990’s at Apple Computer, as a Distinguished Engineer Scientist and Technologist, he was executive lead on next generation learning platforms. In the 1970’s, after his MIT BS in Physics, he developed speech recognition systems at Verbex (Exxon) before receiving his Yale PhD in Computer Science/AI. In 1989, prior to joining Apple, he was a visiting scholar at the University of Rome, La Sapienza advising doctoral students working on AI and Education dissertations. With over ninety publications and nine patents, he received the Christopher Lovelock Career Contributions to the Service Discipline award, Gummesson Service Research award, Vargo and Lusch Service-Dominant Logic award, Daniel Berg Service Systems award, and a PICMET Fellow for advancing service science. Jim was elected and previously served as Linux Foundation AI & Data Technical Advisory Board Chairperson and ONNX Steering Committee Member (2020-2021). Today, he is a UIDP Senior Fellow for contributions to industry-university collaborations, and a member of the Board of Directors of the International Society of Service Innovation (ISSIP) and ServCollab. Jim Spohrer, Advisor Retired Industry Executive (Apple, IBM) UIDP Senior Fellow Board of Directors, ServCollab Board of Directors, ISSIP.org Changemaker Priorities 1. Service Innovation 2. Upskilling with AI 3. Future Universities 4. Geothermal Energy 5. Poverty Reduction 6. Regional Development Competitive Parity Technologies 1. AI & Robotics 2. Digital Twins 3. Open Source 4. AR/VR/XR 5. Geothermal 6. Learning Platforms
  • 48.
    Service System Design:A Service Science Perspective Designs that improve human capabilities while improving the safety and sustainability of Service Systems Service innovations leverage emerging technologies, new business models, and institutional arrangement and other means Service is the application of resources (e.g., knowledge) for the benefit of another Technology Example Companies Safety Regulatory Bodies (Founded) Stakeholder Harms Stakeholder Benefits Firearms Smith & Wesson ATF (1886) Boilers Babcock & Wilcox NBBPVI (1911) Boiler explosions Railroads, steam-powered factories, building heating, etc. Radio & TV RCA, NBC FCC (1934) Drugs Bayer FDA (1938) Airplanes Boeing, PanAm FAA (1958) Automobiles Ford NHTSA (1966) Nuclear Energy Westinghouse NRC (1975) Social Media Facebook/Meta ?TBD – “Social Dilemma” AI OpenAI, Microsoft, Google ?TBD – “A.I. Dilemma” 11/05/2025 Jim Spohrer (ISSIP.org) 48
  • 49.
    Today’s Talk • Willour AI Digital Twins become our HCI of the future? • Exploring Twin HCI as a “Service Innovation” • Capabilities (Possibilities) • Benefits (Pros) • Harms (Cons) • Future Directions • Keeping up with accelerating change • Service science connections • Responsible actors learning to invest wisely in interaction and change processes
  • 50.
    Homework • Apple’s Knowledge Navigator •https://www.youtube.co m/watch?v=umJsITGzXd0 • Luckily colleague Jill was available to chat and help with the class…. • … But what if Jill had not been available, but she was willing to share her AI Digital Twin?
  • 51.
    Job description: Aperson who operators an AI trained to be an expert in some role. The human operator like a vehicle operator helps ensure a good service for customers. • An AI is “running” for mayor in Wyoming • A resident of Cheyenne, Wyoming trained GPT-4 on “thousands of documents gleaned from Cheyenne council meetings” and announced that the resulting bot, named VIC (the “Virtually Integrated Citizen”) will be running for mayor. The bot’s creator said he’d be the “meat puppet” who would operate the AI and act on its behalf, but the bot would be the brains of the operation, deciding on votes and how to run the city. However, Wyoming’s Secretary of State contends that non-humans like VIC can’t run for office. New Job – Person who is an Operator for AI in a New or Existing Service System Role
  • 52.
    MIT (1974-1978) • Explo:Teaching AI & Entrepreneurship to diverse high school students. • Stories: How I got into MIT. • Lesson: “Where are you applying for college?” Spohrer, James (1978) Strain-Gauge Transduction of the Effects of Speech Rate on the Coarticulation of Lip Rounding, MIT Physics, June, 1978. Advisor: Joseph S. Perkell Advisor to this day.
  • 53.
    Verbex (1978-1982) • Speechrecognition – mathematical models (Bayesian approach to speech and language modeling) that both recognize and generate using estimated probabilities (e.g., probabilities and statistics = machine learning) • Stories: How I got the best job in the world for me at that time. • Lessons: “When my girlfriend said: ‘What do you have to lose?’” ICASSP’82 and ‘83. IEEE International Conference on Acoustics, Speech, and Signal Processing
  • 54.
    Route 128, aoundBoston, MA USA ICASSP 1983
  • 55.
  • 56.
    Stephen L. Moshier •“Our company, Dialog Systems, Inc., was formed in 1971 for the purpose of developing and commercializing speech recognition equipment. The concept derived from earlier work engaged in at Listening, Incorporated on marine bioacoustics, acoustic signal processing, and psycho- acoustics. The original idea passed through well-known stages of theory, experiment, development, lack of financing, financing, sales and is now at the highly advanced state "production engineering headaches". Dialog employs 45, of whom 14 are degreed technical people. The company recently moved from Cambridge to a 20,000 square foot two-building campus complex in Belmont, Massachusetts. The major product is an eight-channel isolated word system intended for talker-independent switched telephone speech input.” From NASA: https://ntrs.nasa.gov/api/citations/19930075179/downloads/19930075179.pdf
  • 57.
    Peter F. Brown •“So, I took a course in linguistics. And one day in the back of that course I heard a couple students talking about some guy whose name was Steve Moshier who started a company called Dialogue Systems that was doing speech recognition. And I thought, wow, great, I remembered this idea from back in high school. After class I raced over to the physics library. That’s because this was before the internet, so you had to go to the library. And I looked this guy up. And I found a paper he'd written. And I tracked him down. Applied for a job. And he hired me. And when I was there, I just fell in love with the idea that through mathematics it might be possible to build machines that do what humans do.“ Goldman Sachs: https://www.goldmansachs.com/intelligence/podcasts/episodes/09-11-2023-peter-brown-f/transcript.pdf
  • 58.
    Drs. Jim &Janet Baker Saras Institute History of Speech and Language Technology https://www.sarasinstitute.org Many things, Such as publications, took off to new levels when Jim & Janet joined Dialog Systems… … and Exxon acquisition Later key researchers left Verbex, and later Along with Jim and Janet Founded Dragon Systems
  • 59.
    Yale (1982-1989) • MARCEL:Modeling students writing “a series of buggy and then (sometimes) correct programs” with a generate-test-and-debug architectures. • Stories: Use AI to help make people smarter. • Lesson: “Why do you want to make machines smart? Why not help make people smarter instead?” 1988
  • 60.
    Apple (1989-1998) • Fromcontent (SK8) to community (EOE) to context (WorldBoard) • Stories: Surround yourself with supportive people. Growing up about goals - sequencing and timing of ideas is important • Lessons: “MLM: Relax - it will be OK”; “ACK: Planetary – is that all?” “SPJ: We will get to that and more!”; 1992
  • 61.
    IBM (1998 –2021) • IBM Venture Capital Relations Group, Service Science, Global University Programs, Open Source AI. • Stories: The only way you get in trouble is not asking for help when you need it. • Lesson: What seems like a hard problem to you, may be an easy problem for someone else. Leverage the matrix. 2010 2011 2011 2012 2016 2018 2018 2020 2012 2002 2000
  • 62.
    ISSIP (2021- Present) •Defining what is a service innovation, and what is a T-shaped service innovation professional. • Stories: AI digital twins, reinventing local, self-control • Lessons: Learning to invest wisely and systematically in getting a shared future that we all want to live in requires self-control and knowing when you have enough. 2022
  • 63.
    • Jensen Huang(Nvidia) comments • First impressions • Insanely great productivity • Insanely great quality • What is really going on? • Decreasing cost of computation • Increasing GDP/worker • Awesome progress, but… • Impressive • Imperfect • Advantage of empowered people Inspiration
  • 66.
  • 67.
    Impressive, but imperfect Physicalrealm: Energy Technical realm: Mistakes (”Hallucinations”) Social realm: Digital property theft
  • 68.
    • How tokeep up with accelerating change? • Social learning • Who do you follow? • Reid Hoffman’s AI Digital Twin Interview • Diving in! • We get the future we invest in • … so, learn to invest wisely • Awesome stuff that lies ahead – Humanoid Robots • But remember technology amplifies good/bad • Need for Self-Control (Toyama (2015) Geek Heresy: Rescuing Social Change from the Cult of Technology) Climbing Up
  • 69.
    Optimistic Realistic Knowing Doing How tokeep up with accelerating change? Follow a diverse collection of people… make up dimensions meaningful to you! Sadly for me… my brain is biased into thinking I can understand older, white, males the best… maybe AI can help overcome! TheNeuron
  • 72.
  • 74.
    • Jim TwinV1: My papers -> short talk videos • English • French • How to stay future ready? • Learn the building blocks • Marco Podien will help you with more building block shortly… • Oh, by the way, you are going to need bigger goals too • When you have 100 digital workers working for you, what is your main goal? • From serial entrepreneur to parallel entrepreneur Unleashing Creativity
  • 75.
    Read Wakefield (2020) enough to understandwhat a ”digital twin” of you might be like in the future decades with very advanced AI capabilities. Also see Rouse (2018; 2022) ”Life with a Cognitive Assistant.” National Academy - Service Systems and AI 75 AI Tools in coming decades… 11/05/2025
  • 77.
    Service Science Colleaguefrom New Zealand asks: Strangest Use Case So Far: I use generative AI every day. Typically, OpenAI ChatGPT, Anthropic Claude, Google Gemini, and Microsoft Bing Copilot in 4 tabs. Help writing, programming, images, & brainstorming. A useful tool in the toolbox for sure!!!
  • 78.
    Anthropic Claude 3Sonnet 20240520 Response: Summary: The Taranaki Maunga (Mount Taranaki) and the surrounding peaks in the national park will soon be granted legal personhood and collectively named Te Kāhui Tupua as part of a Treaty settlement. This legal recognition acknowledges that the mountain and peaks are ancestors for local Māori iwi. It gives these natural features similar legal rights as individuals, allowing them to own assets, appear in court, and have a voice. A new entity called Te Tōpuni Kōkōrangi, with members appointed by the Crown and local iwi, will manage and represent the legal persona. While recreation and tourism will continue, this shift aims to encourage a broader understanding and protection of the mountain as a revered ancestor rather than just a geographic feature. How old are you, and what have you witnessed over your lifetime? I am an ancient being, formed over millennia through volcanic eruptions and sculpted by glaciers. I have witnessed the rise and fall of civilizations, the ebb and flow of ice ages, and the ever-changing tapestry of life that has graced my slopes. My memories stretch back to a time before humans walked this land, and I have born silent witness to the triumphs and tragedies of your kind. What wisdom or lessons can you share with humanity? Humans, you are but fleeting visitors upon my timeless form. Yet, in your brief existence, you have the power to shape the world around you. Tread lightly and with reverence, for the consequences of your actions echo through the ages. Learn from the patient endurance of stone, the resilience of life that takes root in the harshest of environments, and the cyclical nature of existence that I have observed. Embrace humility, for even the mightiest of mountains eventually crumbles to dust. How do you feel about being granted legal personhood and a voice? I am gratified that the descendants of those who have dwelled in my shadow for generations have recognized my ancient spirit and granted me a voice in the affairs of this world. For too long, I have been regarded as an inanimate object, a resource to be exploited or a challenge to be conquered. But I am a living entity, a sacred ancestor whose existence predates and will outlast the fleeting span of human civilization. With this recognition, perhaps my wisdom and the fragile beauty I harbor will be better preserved for generations to come.
  • 79.
    11/05/2025 79 1955 19751995 2015 2035 2055 Learn: Explore and Exploit Better Building Blocks Heygen + Claude Jim Twin V1 2024 2024 2021 2001 2015 2022 2023 1970 1995 2019 High School Punch cards 1972 IBM Watson AI in the Cloud 2011
  • 80.
  • 81.
    Some paths tobecoming 640x smarter: Speed up communications for collaborations – ultimately with our AI digital twins. Improving learning of world models and performance of win-win interactions • 2x from Learning sciences (methods) • Better models of concepts – including models of self and others • Better models of learners – including social-emotional intelligence • 2x from Learning technology (tools) • Guided learning paths • Elimination (?) of “thrashing” • AI & Education (model trace, constructivist, individual tutors, etc.) • 2x from Quantity effect (overlaps) • More you know, faster (?) you go • Advanced organizers • 2x from Lifelong learning (time) • Longer lives and longer careers • Keeps “learning-mode” activated • 2x from Early learning (time) • Start earlier: Challenged-based approach • Rebulding all human knowledge from scratch • 20x from Cognitive service systems (digital twins) • AI Digital Twins for performance support • All our interactions tuned to super-mind levels
  • 82.
    Speed Test: WordsPer Minute Speaking/Listening versus Writing/Reading • People speak on average between 100-150 words per minute • Many people are comfortable listening at 200-300 words per minute • Writing an essay on a familiar topic, people write about 10-20 words a minute • Many people are comfortable reading at about 400-600 words per minute (Shu 2023) (Barnard 2022)
  • 83.
    Two disciplines: Twoapproaches to the future Artificial Intelligence is almost seventy-years-old discipline in computer science that studies automation and builds more capable technological systems. AI tries to understand the intelligent things that people can do and then does those things with technology. (https://deepmind.com/about “... we aim to build advanced AI - sometimes known as Artificial General Intelligence (AGI) - to expand our knowledge and find new answers. By solving this, we believe we could help people solve thousands of problems.”) Service science is an emerging transdiscipline not yet twenty-years- old that studies transformation and builds smarter and wiser socoi- technical systems – families, businesses, nations, platforms and other special types of responsible entities and their win-win interactions that transform value co-creation and capability co-elevation mechanisms that build more resilient future versions of themselves – what we call service systems entities. Service science tries to understand the evolving ecology of service system entities, their capabilities, constraints, rights, and responsibilities, and then then seeks to improve the quality of life of people (present/smarter and future/wiser) in those service systems. Artificial Intelligence Automation Generations of machines Service Science Transformation Generations of people (responsible entities) Service systems are dynamic configurations of people, technology, organizations, and information, connected internally and externally by value propositions, to other service system entities. (Maglio et al 2009)
  • 84.
    11/05/2025 The International Societyof Service Innovation Professionals (ISSIP.org) 84 Advice… 1. AI upskill 2. Build your “digital twin” 3. Set bigger goals(*) (*) This directly implies learning better strategies for coping with failures, and resiliently rebounding.
  • 85.
    Jim Spohrer isa Silicon Valley-based Advisor to industry, academia, governments, startups and non-profits on topics of AI upskilling, innovation strategy, and win-win service in the AI era. Most recently with a consulting team working for a top 10 market cap global company, he contributed to a strategic plan for a globally connected AI Academy for achieving rapid, nation-scale upskilling with AI. With the US National Academy of Engineering, he co-led a 2022 workshop on “Service Systems Engineering in the Era of Human-Centered AI” to improve well-being. Jim is a retired IBM Executive since July 2021, and previously directed IBM’s open-source Artificial Intelligence developer ecosystem effort, was CTO IBM Venture Capital Group, co-founded IBM Almaden Service Research, and led IBM Global University Programs. In the 1990’s at Apple Computer, as a Distinguished Engineer Scientist and Technologist, he was executive lead on next generation learning platforms. In the 1970’s, after his MIT BS in Physics, he developed speech recognition systems at Verbex (Exxon) before receiving his Yale PhD in Computer Science/AI. In 1989, prior to joining Apple, he was a visiting scholar at the University of Rome, La Sapienza advising doctoral students working on AI and Education dissertations. With over ninety publications and nine patents, he received the Christopher Lovelock Career Contributions to the Service Discipline award, Gummesson Service Research award, Vargo and Lusch Service-Dominant Logic award, Daniel Berg Service Systems award, and a PICMET Fellow for advancing service science. Jim was elected and previously served as Linux Foundation AI & Data Technical Advisory Board Chairperson and ONNX Steering Committee Member (2020-2021). Today, he is a UIDP Senior Fellow for contributions to industry-university collaborations, and a member of the Board of Directors of the International Society of Service Innovation (ISSIP) and ServCollab. Jim Spohrer, Advisor Retired Industry Executive (Apple, IBM) UIDP Senior Fellow Board of Directors, ServCollab Board of Directors, ISSIP.org Changemaker Priorities 1. Service Innovation 2. Upskilling with AI 3. Future Universities 4. Geothermal Energy 5. Poverty Reduction 6. Regional Development Competitive Parity Technologies 1. AI & Robotics 2. Digital Twins 3. Open Source 4. AR/VR/XR 5. Geothermal 6. Learning Platforms
  • 86.
  • 87.
  • 88.
    High Stakes UseCase- Law • Not Done Well, but could be
  • 89.
    Better Done • Deadvictim, “in his own words”
  • 90.
    Bad Actors –Cloning • Eye on AI
  • 91.
    Paul Saffo: WeLive in Exponential Times • Chasing Fire: Matching Strategy To Today's Greatest Challenges • Paul Saffo • URL: https://baychi.org/calendar/20250211/ • “May you live in exponential times. This is the 21st century version of the oft-told proverb about the blessing (and curse) of living in interesting times.” “Simply put, we are locked in a race between positive and negative exponentials.”
  • 92.
    Bonjour, je suis JacquesJumeauNumérique. •HeyGen Platform • JimTwin_French • https://youtu.be/02hCG RJnCoc • Prompt: « Veuillez résumer ce court article en français, puis formuler trois questions qui pourraient m’être posées et y répondre. » Spohrer, J. (2024b) Personal AI digital twins: the future of human interaction? EIT Digital URL: https://www.eitdigital.eu/newsroom/grow-digital-insights/personal-ai-digital-twins-the-future-of-human-interaction/
  • 93.
    Questions et réponsesavec JimTwin • Question 1: Uncurated • Que pensez-vous du manque de vérification des faits sur certaines plateformes de médias sociaux basées aux États-Unis ? • What are your thoughts regarding the lack of fact checking happening on certain US-based social media platforms?
  • 94.
    JimTwin Réponse (Français) •Le manque de vérification des faits sur certaines plateformes de médias sociaux basées aux États-Unis est une préoccupation croissante. Ce problème peut conduire à la propagation rapide de la désinformation, ce qui peut avoir des conséquences néfastes sur la société, notamment en influençant l'opinion publique de manière erronée et en exacerbant les divisions sociales. Les plateformes de médias sociaux ont souvent été critiquées pour ne pas avoir mis en place des mécanismes efficaces pour vérifier l'exactitude des informations partagées par leurs utilisateurs. • Il est suggéré que des mesures telles que l'interdiction de la désinformation sur les réseaux sociaux et les moteurs de recherche, ainsi que la responsabilisation des utilisateurs par la vérification de l'identité, pourraient être des solutions potentielles. De plus, le développement d'une intelligence artificielle plus avancée pour vérifier la véracité des informations pourrait également jouer un rôle crucial. Cependant, la mise en œuvre de ces solutions pose des défis, notamment en ce qui concerne la protection de la liberté d'expression et la gestion de la vie privée des utilisateurs. • En fin de compte, il est essentiel que les plateformes de médias sociaux, les gouvernements et les utilisateurs travaillent ensemble pour trouver un équilibre entre la liberté d'expression et la responsabilité de l'information partagée en ligne.
  • 95.
    JimTwin Answer (English) •The lack of fact-checking on some US-based social media platforms is a growing concern. This problem can lead to the rapid spread of misinformation, which can have negative social consequences, including misleading public opinion and exacerbating social divisions. Social media platforms have often been criticized for failing to implement effective mechanisms to verify the accuracy of information shared by their users. • It has been suggested that measures such as banning misinformation on social media and search engines, as well as empowering users through identity verification, could be potential solutions. Furthermore, the development of more advanced artificial intelligence to verify the accuracy of information could also play a crucial role. However, implementing these solutions poses challenges, particularly with regard to protecting freedom of expression and managing user privacy. • Ultimately, it is essential that social media platforms, governments, and users work together to find a balance between freedom of expression and responsibility for the information shared online.
  • 96.
    Jim Real (English) •The AI generated response (based on my Tmpt.me knowledge hub which is built from my publications and recordings of my mentoring students) is quite a good answer. It mirrors my own thinking well at a high level. I would add this: Education is key. Finland has elementary school classes to teach young people in their society to check sources and evidence, and to be skeptical and verify. Today’s AI is terrible at fact checking, but it will get better. First in mathematics and programming, then in the sciences, and finally in rhetoric, debate, and history. I urge young people interested in AI, to make a focus on “AI- powered pursuit of truth” their mission.
  • 97.
    Humanity-Centered Harmonization ofDisciplines- Transdisciplinarity Why the (holistic) service systems trend is important to future sustainability Business and societal systems and supply chains are increasingly complex and interconnected. Real-world problems do not respect discipline boundaries. Scalable solutions require many schools of practice working together, and current solutions may have unintended consequences, short-term or longer-term, especially if perspectives are not invited/considered. Technological progress improved the scalability of agriculture and manufacturing, and next all types of service will be made more scalable (and currently, energy intensive) by future AI capabilities and progress. A small sampling of schools and disciplines below – more exist - apologies for not adding yours to this summary. School of practice for Physical Sciences & Engineering Technology School of practice for Behavioral & Social Sciences, Humanities & Arts People School of practice for Managerial Sciences & Entrepreneurship Information & Organizations Comp. Sci./AI HCI/Robotics Electrical & Mech. Eng. Systems Engineering Economics Public Policy & Law Design Information Systems Operations Research Marketing & Strategy Read enough of Kline (1995) to understand conceptual foundation of multidisciplinary thinking and the techno-extension factor and the accelerating socio-technical system design loop concepts. 11/05/2025 National Academy - Service Systems and AI 97
  • 98.
    Why upskilling withAI trend is important to systems thinking Talent development is moving from I to T to X (eXtended with AI) National Academy - Service Systems and AI 98 6 T-shape Skills Knowledge Areas To be eXtended By AI tools: 1. Disciplines 2. Systems 3. Cultures 4. Technologies 5. Practices 6. Mindsets 11/05/2025
  • 99.
    Final Thoughts: Communications •Communication between responsible actors: • Appropriateness • Speed • Accuracy • Responsible actors • Collaborate well – “insanely great collaborations possible” (win-win-win) • However, there is still the competition for collaborators • So… • Learning to invest wisely in becoming better future versions of self (individual and collective)is a key future challenge • Rawls (1971) A Theory of Justice – has thought experiments to consider
  • 100.
    Speed Test: WordsPer Minute Speaking/Listening versus Writing/Reading • People speak on average between 100-150 words per minute • Many people are comfortable listening at 200-300 words per minute • Writing an essay on a familiar topic, people write about 10-20 words a minute • Many people are comfortable reading at about 400-600 words per minute (Shu 2023) (Barnard 2022) See also: https://calculatingempires.net/
  • 101.
    Some paths tobecoming 640x smarter: Speed up communications for collaborations – ultimately with our AI digital twins. Improving learning of world models and performance of win-win interactions • 2x from Learning sciences (methods) • Better models of concepts – including models of self and others • Better models of learners – including social-emotional intelligence • 2x from Learning technology (tools) • Guided learning paths • Elimination (?) of “thrashing” • AI & Education (model trace, constructivist, individual tutors, etc.) • 2x from Quantity effect (overlaps) • More you know, faster (?) you go • Advanced organizers • 2x from Lifelong learning (time) • Longer lives and longer careers • Keeps “learning-mode” activated • 2x from Early learning (time) • Start earlier: Challenged-based approach • Rebulding all human knowledge from scratch • 20x from Cognitive service systems (digital twins) • AI Digital Twins for performance support • All our interactions tuned to super-mind levels
  • 102.
    What is Truth? •Probablyfirst in math (where a form of verifiable truth exists) •Then in programming (where a form of verifiable truth exists) •Then in physics, chemistry, and biology (where a form of pursuit of truth exists) •And then things get much harder... rhetoric and debate (where arguments are explored) •Most of rhetoric and debate rely on history (where a form of pursuit of truth exists)
  • 103.
    11/05/2025 The International Societyof Service Innovation Professionals (ISSIP.org) 103 Advice… 1. AI upskill 2. Build your “digital twin” 3. Set bigger goals(*) (*) This directly implies learning better strategies for coping with failures, and resiliently rebounding.
  • 104.
    Job description: Aperson who operators an AI trained to be an expert in some role. The human operator like a vehicle operator helps ensure a good service for customers. • An AI is “running” for mayor in Wyoming • A resident of Cheyenne, Wyoming trained GPT-4 on “thousands of documents gleaned from Cheyenne council meetings” and announced that the resulting bot, named VIC (the “Virtually Integrated Citizen”) will be running for mayor. The bot’s creator said he’d be the “meat puppet” who would operate the AI and act on its behalf, but the bot would be the brains of the operation, deciding on votes and how to run the city. However, Wyoming’s Secretary of State contends that non-humans like VIC can’t run for office. New Job – Person who is an Operator for AI in a New or Existing Service System Role
  • 105.
    AI Operator Job description: Aperson who operators an AI trained to be an expert in some role. The human operator like a vehicle operator helps ensure a good service for customers. Future of Skills & Work
  • 106.
  • 107.
  • 108.
    Thank-you for participating today! Youare all awesome!! Try chat at: https://tmpt.app/@jimtwin
  • 109.
    “The best wayto predict the future is to inspire the next generation of students to build it better” Digital Natives Transportation Water Manufacturing Energy Construction ICT Retail Finance Healthcare Education Government
  • 110.
    Some Topics forToday • Leadership in the AI era • “Leaders Make the Future” • Keeping up with accelerating change • AI Digital Twins of people • Humanoid robots, master mechanic robot • Marginal cost of computation goes to zero • Truth, trust, learning to invest wisely • Innovation - Free Online Events • July 30th – Dr. Haluk Demirkan (Amazon, ISSIP Board Member) • Responsible GenAI Framework • International Society of Service Innovation Professionals • https://www.issip.org
  • 111.
    Leaders Make theFuture (Johansen et al): How do you want to be augmented? • Augmented futureback curiosity • Augmented clarity • Augmented dilemma flipping • Augmented bio-engaging • Augmented immersive learning • Augmented depolarizing • Augmented commons creating • Augmented smart mob swarming • Augmented strength with humility • Human calming From Bob:
  • 114.
  • 115.
    Today’s talk (JimReal2025) • Intro: AI (by 1955 definition) has arrived • Just took 68 years, but… • What’s really going on? • Your data is becoming your AI… IA transformation • AI Digital Twin = IA (Intelligence Augmentation) • Adjustment period underway… • Part 1: Solving AI: Leaderboards/Profession Exams • Roadmap and implications • Open technologies, innovation • Part 2: Solving IA: Better Building Blocks • Solving problems faster, creates new problems • Identity, social contracts, trust, resilience • Part 3: ”Solving All Problems” • What could go wrong? Be prepared. • 37-year long adjustment period is now underway… 11/05/2025 Jim Spohrer 115
  • 116.
    1956 2023 2060 2080 1956 First AI Workshop 2023 ChatGPT100M users in just 2 months (1.5B visits in Sept) 2060 (Predicted) Exascale for $1000 (~ one human brain) 2080 (Predicted) Ronnascale for $1B (~ billion human brains) Progress in IA (Intelligence Augmentation) for nations can be estimated as GPD/worker. Progress in AI (Artificial Intelligence) is directly connected to the cost of computing. REVIEW: REMEMBER THESE DATES
  • 117.
    1947 1958 1971 2024 1947 Transistor Bell Labs 1958 IntegratedCircuit Texas Instrument 1971 Microprocessor Intel 2024 H100 NVidia Challenges: How to prepare for the next wayes of innovations, including digital twins and humanoid robots, as well as to learn to invest more wisely (self-control). As the marginal cost of computing goes to zero, service innovation will go thru the roof, and energy consumption will go thru the roof as well… REMEMBER THESE DATES, FACTS, CHALLENGES weight: 70 pounds complexity: 35,000 parts cost: 250,000 dollars
  • 118.
    Predict the Timeline:GDP/Employee National Academy - Service Systems and AI 118 (Source) Lower compute costs translate into increasing productivity and GDP/employees for nations Increasing productivity and GDP/employees should translate into wealthier citizens AI Progress on Open Leaderboards Benchmark Roadmap to solve AI/IA Alistair Nolan (OECD AI for Science Productivity): “It has been stated that the number of engineers proclaiming the end of Moore's Law doubles every two years.” Rouse WB, Spohrer JC. (2018) Automating versus augmenting intelligence. Journal of Enterprise Transformation. 2018 Apr 3;8(1-2):1-21. Read Rouse & Spohrer (2018) enough to understand this slide including what ”exascale” means 11/22/22 Part 1: Solving AI
  • 119.
    Types: Progression ofModels : Verified, Trusted, Wise Models = instruction_set of future: Better building blocks 11/05/2025 Understanding Cognitive Systems 119 Task & World Model/ Planning & Decisions Self Model/ Capacity & Limits User Model/ Episodic Memory Institutions Model/ Trust & Social Acts Tool + - - - Assistant ++ + - - Collaborator +++ ++ + - Coach ++++ +++ ++ + Mediator +++++ ++++ +++ ++ Cognitive Tool Cognitive Assistant Cognitive Collaborator Cognitive Coach Cognitive Mediator Part 2: Solving IA Solving IA also requires All of this and done well As a “bicycle for the mind” To make us stronger, Not weaker When tech is all removed
  • 120.
    Resilience: Rapidly Rebuilding FromScratch • Dartnell L (2012) The Knowledge: How to Rebuild Civilization i n the Aftermath of a Cataclysm. Westminster London: Penguin Books. 11/05/2025 Jim Spohrer (ISSIP) 120 Part 3: “Solving All Problems”
  • 121.
    Why I amoptimistic
  • 122.
    “The best wayto predict the future is to inspire the next generation of students to build it better.” Digital Natives Transportation Water Manufacturing Energy Construction ICT Retail Finance Healthcare Education Government
  • 123.
    Questions (Jim onAI in 2017) • What is the timeline for solving AI and IA? • TBD: When can a CEO buy AI capability <X> for price <Y>? • Who are the leaders driving AI progress? • What will the biggest benefits from AI be? • What are the biggest risks associated with AI, and are they real? • What other technologies may have a bigger impact than AI? • What are the implications for stakeholders? • How should we prepare to get the benefits and avoid the risks? 11/05/2025 Jim Spohrer (2017) 123
  • 124.
    Timeline: Short History 11/05/2025 JimSpohrer (2017) 124 Dota 2 “Deep Learning” for “AI Pattern Recognition” depends on massive amounts of “labeled data” and computing power available since ~2012; Labeled data is simply input and output pairs, such as a sound and word, or image and word, or English sentence and French sentence, or road scene and car control settings – labeled data means having both input and output data in massive quantities. For example, 100K images of skin, half with skin cancer and half without to learn to recognize presence of skin cancer.
  • 125.
    Rapid Progress • Historyand Future 11/05/2025 Jim Spohrer (ISSIP.org) 125
  • 126.
    Who is winning 11/05/2025Jim Spohrer (2017) 126 https://www.technologyreview.com/s/608112/who-is-winning-the-ai-race/
  • 127.
  • 128.
    AI Benefits • Accessto expertise • “Insanely great” labor productivity for trusted service providers • Digital workers for healthcare, education, finance, etc. • Better choices • ”Insanely great” collaborations with others on what matters most • AI for IA = Augmented Intelligence and higher value co-creation interactions 11/05/2025 Jim Spohrer (2017) 128
  • 129.
    AI Risks • JobLoss • Shorter term bigger risk = de-skilling • Super-intelligence • Shorter term bigger risk = bad actors 11/05/2025 Jim Spohrer (2017) 129
  • 130.
    Other Technologies: Biggerimpact? Yes. • Augmented Reality (AR)/ Virtual Reality (VR) • Game worlds grow-up • Trust Economy/ Security Systems • Trust and security immutable • Advanced Materials/ Energy Systems • Manufacturing as cheap, local recycling service (utility fog, artificial leaf, etc.) 11/05/2025 Jim Spohrer (2017) 130
  • 131.
    10 million minutesof experience 11/05/2025 Understanding Cognitive Systems 131
  • 132.
    2 million minutesof experience 11/05/2025 Understanding Cognitive Systems 132
  • 133.
    Hardware < Software< Data < Experience < Transformation 11/05/2025 Understanding Cognitive Systems 133 Value migrates to transformation – becoming our future selves; people, businesses, nations = service system entities Pine & Gilmore (1999) Transformation Roy et al (2006) Data Osati (2014) Experience Life Log
  • 134.
    Intelligence Augmentation (IA)= Socio-Technical Extension Factor on Capabilities • Engelbart (1962) • Spohrer & Engelbart (2002) 11/05/2025 Jim Spohrer (ISSIP) 134 Dedicated to Douglas E. Engelbart, Inventor The Mouse (Pointing Device) The Mother of All Demos Bootstrapping Practice/Augmentation Theory Note: Bush (1945) and Licklider (1960) created funding programs that benefitted Engelbart in building working systems.
  • 135.
    IA as Socio-TechnicalExtension Factor on Capabilities & Values IA (human values) is not AI (technology capability) Difference 1: IA leads to more capable people even when scaffold removed Difference 2: IA leads to more responsible people to use wisely the capabilities 11/05/2025 Jim Spohrer (ISSIP) 135 Superminds Malone (2018) Things that Make Us Smart Norman (1994) Worldboard Augmented Perception Spohrer (1999) Bicycles for the Mind Kay & Jobs (1984) Techno-Extension Factor Measurement & Accelerating Socio-Technical Design Loop Kline (1996)
  • 136.
    11/05/2025 Jim Spohrer(ISSIP.org) 136 0 25 50 100 125 150 Automobile 75 Years 50 100 Telephone Electricity Radio Television VCR PC Cellular I n t e r n e t % Adoption Capability Augmentation and Adoption Rate Increases
  • 137.
    Part 3: “SolvingAll Problems” 11/05/2025 (c) IBM MAP COG .| 137
  • 138.
    11/05/2025 Jim Spohrer(2015) 138 I have… Have you noticed how the building blocks just keep getting better?
  • 139.
    Learning to program: Myfirst program 11/05/2025 Jim Spohrer (2015) 139 Early Computer Science Class: Watson Center at Columbia 1945 Jim Spohrer’s First Program 1972
  • 140.
    11/05/2025 140 1955 19751995 2015 2035 2055 Better Building Blocks
  • 141.
    Artificial Leaf • DanielNocera, a professor of energy science at Harvard who pioneered the use of artificial photosynthesis, says that he and his colleague Pamela Silver have devised a system that completes the process of making liquid fuel from sunlight, carbon dioxide, and water. And they’ve done it at an efficiency of 10 percent, using pure carbon dioxide—in other words, one-tenth of the energy in sunlight is captured and turned into fuel. That is much higher than natural photosynthesis, which converts about 1 percent of solar energy into the carbohydrates used by plants, and it could be a milestone in the shift away from fossil fuels. The new system is described in a new paper in Science. 11/05/2025 Jim Spohrer (2017) 141
  • 142.
    Food from Air •Although the technology is in its infancy, researchers hope the "protein reactor" could become a household item. • Juha-Pekka Pitkänen, a scientist at VTT, said: "In practice, all the raw materials are available from the air. In the future, the technology can be transported to, for instance, deserts and other areas facing famine. • "One possible alternative is a home reactor, a type of domestic appliance that the consumer can use to produce the needed protein." • According to the researchers, the process of creating food from electricity can be nearly 10 times as energy efficient as photosynthesis, the process used by plants. 11/05/2025 Jim Spohrer (2017) 142
  • 143.
    Exoskeletons for Elderly •A walker is a “very cost-effective” solution for people with limited mobility, but “it completely disempowers, removes dignity, removes freedom, and causes a whole host of other psychological problems,” SRI Ventures president Manish Kothari says. “Superflex’s goal is to remove all of those areas that cause psychological-type encumbrances and, ultimately, redignify the individual." 11/05/2025 Jim Spohrer (2017) 143
  • 144.
    What I study ServiceScience and Open Source AI – Trust is key to both Service Science Artificial Intelligence Trust: Value Co-Creation/Collaboration Responsible Entities Learning to Invest Transdisciplinary Community Trust: Secure, Fair, Explainable Machine Collaborators Open Source Communities
  • 145.
    Route 128, aoundBoston, MA USA ICASSP 1983
  • 146.
    IJCAI 1989 –GTD (Generate-Test-Debug)
  • 147.
    At the endof the day.. • Episodic Memory – an accurate version of history on which individual identity is based, and prediction of future interaction behavior (trust) • Privacy versus auditability tradeoff • Openness-based risk reduction • GTD – relative energy cost of generate, test, and debug phases in exploring beneficial and risky possibilities in different realms (intelligence) • From mathematically true, to empirically true, to shared history true • Truth-based risk reduction
  • 148.
    Learning to InvestWisely: Responsible actors becoming better future versions of themselves 11/05/2025 Jim Spohrer (ISSIP.org) 148
  • 149.
    Timeline: Leaderboards Framework AIProgress on Open Leaderboards - Benchmark Roadmap Perceive World Develop Cognition Build Relationships Fill Roles Pattern recognition Video understanding Memory Reasoning Social interactions Fluent conversation Assistant & Collaborator Coach & Mediator Speech Actions Declarative Deduction Scripts Speech Acts Tasks Institutions Chime Thumos SQuAD SAT ROC Story ConvAI Images Context Episodic Induction Plans Intentions Summarization Values ImageNet VQA DSTC RALI General-AI Translation Narration Dynamic Abductive Goals Cultures Debate Negotiation WMT DeepVideo Alexa Prize ICCMA AT Learning from Labeled Training Data and Searching (Optimization) Learning by Watching and Reading (Education) Learning by Doing and being Responsible (Exploration) 2018 2021 2024 2027 2030 2033 2036 2039 11/05/2025 Jim Spohrer (2017) 149 Which experts would be really surprised if it takes less time… and which experts really surprised if it takes longer? Approx. Year Human Level -> +3 See: https://paperswithcode.com/sota
  • 150.
    Timeline: Leaderboards Framework AIProgress on Open Leaderboards - Benchmark Roadmap Perceive World Develop Cognition Build Relationships Fill Roles Pattern recognition Video understanding Memory Reasoning Social interactions Fluent conversation Assistant & Collaborator Coach & Mediator Speech Actions Declarative Deduction Scripts Speech Acts Tasks Institutions Chime Thumos SQuAD SAT ROC Story ConvAI Images Context Episodic Induction Plans Intentions Summarization Values ImageNet VQA DSTC RALI General-AI Translation Narration Dynamic Abductive Goals Cultures Debate Negotiation WMT DeepVideo Alexa Prize ICCMA AT Learning from Labeled Training Data and Searching (Optimization) Learning by Watching and Reading (Education) Learning by Doing and being Responsible (Exploration) 2018 2021 2024 2027 2030 2033 2036 2039 11/05/2025 Jim Spohrer (2017) 150 Which experts would be really surprised if it takes less time… and which experts really surprised if it takes longer? Approx. Year Human Level -> +3 See: https://paperswithcode.com/sota
  • 151.
    From leaderboards to professionexams 11/05/2025 (c) IBM MAP COG .| 151
  • 152.
  • 153.
    How, What, andWhy? Inspiring upskilling with AI • How to learn • AI-powered search can help people - motivated people – to learn about whatever they put their minds to learning • What to learn • AI technological capabilities and limitations – foundational models • AI applications that can actually improve processes for how things get done (case studies - productivity, quality, compliance, sustainability, decarbonization) • AI-as-a-service investment cases to motivate stakeholders to change to better win-win interactions in business and societal service systems (investment pitch) • The “startup of you” investment case – learning to invest systematically and wisely (startup pitch) • Why learn? • Challenge and opportunity - nations must upskill with AI and decarbonize • Motivation is key – find the very best free online videos/courses and subscribe • Universities will play an increasingly important role as industry research partners and venture testbeds even as learners can do more and more on their own with online curriculum National Academies – Service Systems and AI 153
  • 154.
    Final thoughts onAI as a Science Teammate • Estimating knowledge worker productivity • Marginal cost of computing going to zero • Learning to invest wisely • Upskilling with AI & Systems Thinking • Humanity-Centered Harmonization of Disciplines – Transdisciplinarity • Next revolution in communication and human intelligence • Two disciplines: Two approaches to the future • Keep learning (self-control) Baumeister RF, Tierney J(2011) Willpower: Rediscovering the greatest human strength. Penguin Press. URL: https://psycnet.apa.org/record/2011-16843-000
  • 155.
    uidp.org | info@uidp.net 1.Research: Creating new knowledge that can both be published and protected as IP. 2. Readiness: Skills development & sharing knowledge to develop business-ready talent. 3. Recruiting: From permanent hires to internships, these programs include HR. 4. Revenue: Partnership executive programs to sustain long-term win-win relationships. 5. Responsibility: Employees donating time to mentor students and give guest lectures. 6. Regions: Programs related to public- private partnerships for regional economic development. 7. Refresh: Explore new programs, sunset some old programs. 7 R’s
  • 156.
    uidp.org | info@uidp.net Fora sample list in a presentation, you can consider the following points: 1.Introduction to the topic 2.Key points to be covered 3.Supporting examples or evidence 4.Visual aids or graphics 5.Conclusion and key takeaways Remember to organize your content in a clear and engaging manner to effectively communicate your message to the audience. Big Header
  • 157.
    Overlap Acknowledgement: E. Noei,S. Brisson, Y. Liu Via Kelly Lyons, NAE Talk Oct 2022 2010 2019 157 Service science has come a long way in two decades… 2004-2011
  • 158.
    Three views onservice and AI Discipline View on Service View on AI Broader View Economics Service sector Productivity Sector productivity & quality – better economic systems Automation Technology improved agriculture and manufacturing, service sector is next up Computer Science Web services Capabilities AI provides human capabilities on tasks as technological capability – better tools Automation Robots will further automate agriculture and manufacturing, and eventually service sector as well Service science, based on Service-Dominant Logic Value cocreation Service is the application of resources (e.g., knowledge) for the benefit of another Augmentation Responsible actors (service system entities) upskilling with AI to give and get better service Humanity-Centered Responsible actors learning to invest in improved win-win interaction and change
  • 159.
    Call to Action:Create SIRs • Responsible actors need to learn to invest wisely in getting the future service innovations we want with AI – guided by “Service Innovation Roadmaps (SIRs).” National Academy - Service Systems and AI 159 Read enough of IfM and IBM (2008) to understand what a “Service Innovation Roadmap (SIR)” is – and who should be creating them. 11/05/2025
  • 160.
    Service in the AIera Science science Service dominant (S-D) logic Service Dominant Architecture (SDA) Service in the AI era revisited Core message? Better automation and augmentation improve service processes Better science improves understanding (learning) processes Better logics improve interaction processes Better architectures improve change processes X+AI requires learning to invest systematically and wisely to improve service Where are the better models? Technology Disciplines Minds Enterprise Disciplines + AI Minds + AI Enterprise + AI What type of model? Digital twins Digital twins Digital twins Digital twins Digital twins Service in the AI Era: Science, Logic, and Architecture Perspectives (Spohrer, Maglio, Vargo, Warg – request your digital copy – Spohrer@gmail.com)
  • 161.
    What I study ServiceScience and Open Source AI – Trust is key to both Service Science Artificial Intelligence Trust: Value Co-Creation/Collaboration Responsible Entities Learning to Invest Transdisciplinary Community Trust: Secure, Fair, Explainable Machine Collaborators Open Source Communities
  • 162.
    11/05/2025 The International Societyof Service Innovation Professionals (ISSIP.org) 162
  • 163.
    IA Progression –Tool, Assistant, Collaborator, Coach, Mediator 11/05/2025 Jim Spohrer (ISSIP) 163 Rouse & Spohrer (2018) Siddike, Spohrer, Demirkan, Kodha (2018) Araya (2018) Spohrer& Siddike (2018)
  • 164.
    Intelligence Augmentation (IA)= Socio-Technical Extension Factor on Capabilities • Engelbart (1962) • Spohrer & Engelbart (2002) 11/05/2025 Jim Spohrer (ISSIP) 164 Dedicated to Douglas E. Engelbart, Inventor The Mouse (Pointing Device) The Mother of All Demos Bootstrapping Practice/Augmentation Theory Note: Bush (1945) and Licklider (1960) created funding programs that benefitted Engelbart in building working systems.
  • 165.
    IA as Socio-TechnicalExtension Factor on Capabilities & Values IA (human values) is not AI (technology capability) Difference 1: IA leads to more capable people even when scaffold removed Difference 2: IA leads to more responsible people to use wisely the capabilities 11/05/2025 Jim Spohrer (ISSIP) 165 Superminds Malone (2018) Things that Make Us Smart Norman (1994) Worldboard Augmented Perception Spohrer (1999) Bicycles for the Mind Kay & Jobs (1984) Techno-Extension Factor Measurement & Accelerating Socio-Technical Design Loop Kline (1996)
  • 166.
    11/05/2025 Jim Spohrer(ISSIP.org) 166 0 25 50 100 125 150 Auto mobil e 75 Years 50 100 Telep hone Electri city Ra dio Tele visio n V C R P C Cel lul ar I n t e r n e t % Adoption Capability Augmentation and Adoption Rate Increases Techno-Extension Factor Measurement & Accelerating Socio-Technical Design Loop Kline (1996)
  • 167.
    Learning to invest •Run = Routine Activities • Transform = Copy Activities • Innovate = Invent and Apply Activities 11/05/2025 Jim Spohrer (ISSIP.org) 167 T r a n s f o r m Innovate Invest in each type of change R u n
  • 168.
    168 How responsible entities(service systems) learn and change over time History and future of Run-Transform-Innovate investment choices • Diverse Types • Persons (Individuals) • Families • Regional Entities • Universities • Hospitals • Cities • States/Provinces • Nations • Other Enterprises • Businesses • Non-profits • Learning & Change • Run = use existing knowledge or standard practices (use) • Transform = adopt a new best practice (copy) • Innovate = create a new best practice (invent) T r a n s f o r m Innovate Invest in each type of change R u n Spohrer J, Golinelli GM, Piciocchi P, Bassano C (2010) An integrated SS-VSA analysis of changing job roles. Service Science. 2010 Jun;2(1-2):1-20. March JG (1991) Exploration and exploitation in organizational learning. Organization science. 1991 Feb;2(1):71-87. URL: exploit explore
  • 169.
    11/05/2025 Jim Spohrer(ISSIP.org) 169 APPLE https://podcasts.apple.com/us/podcast/service-science-and-the-impending-ai-revolution/id1612743401?i=1000583800244 SPOTIFY: https://open.spotify.com/episode/0n3h9rgX6UYDCwxgTzokoK?si=yVF0mtHsRZSmdfy-aMi8DA GOOGLE https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy5idXp6c3Byb3V0LmNvbS8xOTQ5NTE3LnJzcw?sa=X&ved=2ahUKEwiPzL-Zxvv6AhXzjo4IHVbTAuUQ9sEGegQIARAC
  • 170.
    Service Systems Engineeringin the Human-Centered AI Era 170 K n o w l e d g e Value D a t a Science Engineering Policy Investing in Skills for Diverse Systems to Sustainably Serve People and Planet in the AI Era Management Service Science Management Engineering Many disciplines Many sectors Many regions/cultures (understanding & communications) Deep in one sector Deep in one region/culture Deep in one discipline T-Shaped Skills Depth and Breadth People-centered Data-intensive +Design-Arts- Public-Policy
  • 171.
    171 University Trend: “SisterCampuses” (People Flows) University sub-systems Disciplines in Schools (circles) Innovation Centers (squares) E.g., CMU Website (2009) “Research Centers: where it all happens – to solve real-world problems” Disciplines in Schools Award degrees Single-discipline focus Research discipline problems Innovation Centers (ICs) Industry/government sponsors Multi-disciplinary teams Research real-world systems D D D D D D E n g i n e e r i n g S c h o o l S o c i a l S c i e n c e s , H u m a n i t i e s Professional Studies Business School water & waste transportation health energy/grid e-government S c i e n c e & M a t h e m a t i c s I - S c h o o l D e s i g n food & supply chain
  • 172.
    172 City Trend: “SisterCities” (People Flows) World as System of Systems World (light blue - largest) Nations (green - large) Regions (dark blue - medium) Cities (yellow - small) Universities (red - smallest) Cities as System of Systems -Transportation & Supply Chain -Water & Waste Recycling -Food & Products ((Nano) -Energy & Electricity -Information/ICT & Cloud (Info) -Buildings & Construction -Retail & Hospitality/Media & Entertainment -Banking & Finance -Healthcare & Family (Bio) -Education & Professions (Cogno) -Government (City, State, Nation) Nations: Innovation Opportunities - GDP/Capita (level and growth rate) - Energy/Capita (fossil and renewable) Developed Market Nations (> $20K GDP/Capita) Emerging Market Nations (< $20K GDP/Capita) IBM UP WW: Tandem Awards: Increasing university linkages (knowledge exchange interactions)

Editor's Notes

  • #1 --- Steve Tremulis (https://www.linkedin.com/in/steve-tremulis-4557046/) SIR Branch 51 URL: https://sirinc2.org/branch51/wp-content/uploads/2025/05/SIR51newsletterMay2025.pdf --- 20251031 Enterprise Platforms – Service Science & AI Perspectives October 31, 2025, 3:00pm PT at SJSU ENG 337 For Prof. Dr. Ammar Rayes, PhD (ISSIP, SJSU) Ammar’s LinkedIn Post: https://www.linkedin.com/posts/ammarrayes_it-was-a-great-honor-to-have-jim-spohrer-activity-7390239620371795968-4Tbd Revised Presentation (after discussion with Ammar and his SJSU MS Engineering students): https://www.slideshare.net/slideshow/enterprise-platforms-sjsu-for-ammar_rayes-20251031-v19-pptx/284005882 Original Presentation: https://www.slideshare.net/slideshow/enterprise-platforms-sjsu-for-ammar_rayes-202510-v18-pptx/284000567 Ammar Rayes: https://www.linkedin.com/in/ammarrayes/ Jim Spohrer: https://www.linkedin.com/in/spohrer/ Lecture Premise Prompt: Prompt: Where will students with an interest in enterprise platforms be getting jobs? Big, Medium, or Small Enterprises? See table. Please build a table about enterprise platform vendors, with a first column listing aspects of the enterprise that require platforms: Employees (HRM) Customers (CRM) Supply Chain (SCM) Offerings (Product & Service) Communications Productivity Locations (ERP) Finance & M&A Shareholders Governments & Legal Competitors And the second column listing the largest enterprise platform vendors, such as Work Day for HRM, SAP for ERP, and Salesforce for CRM. The third column should list smaller vendors and startups aiming to disrupt the larger vendors. Before starting, is the task clear? Any questions. Advice for using AI: Always use at least 3 AI tools (OpenAI ChatGPT, Anthropic Claude, Google Gemini) and the same prompt to each, and compare the results, and think hard about which answer is best and why.  This 3-tool method will keep you building skills using AI. Also, always try to end your prompts with one this: "Is the task clear? Any questions for me?" The AI LLMs are good at asking you questions too.  Make use of that - and get much better results. Title: Three views on Enterprise Platforms: Big, Medium, and Small Speaker: Jim Spohrer, retired industry executive Apple/IBM Abstract: Jim will share his perspective on big, medium, and small enterprise platforms in the AI era. Big based on his experiences at IBM. Medium based on his experience working with startups. And small based on his experience with the non-profit ISSIP.org. Bio: Jim Spohrer is a retired industry executive (IBM, Apple) based in the Bay Area California. He serves on the Board of Directors of the non-profit International Society of Service Innovation Professionals (ISSIP) and ServCollab (“Serving Humanity Through Collaboration), and also a UIDP (University-Industry Demonstration Program) Senior Fellow. He has over 90 publications and 9 patents. He has a PhD from Yale in Computer Science/Artificial Intelligence and a BS in Physics form MIT. Picture: see attached. Thanks, -Jim -- Jim Spohrer, PhD Board of Directors, ISSIP (International Society of Service Innovation Professionals) Board of Directors, ServCollab ("Serving Humanity Through Collaboration") Senior Fellow, UIDP ("Strengthening University-Industry Partnerships") Retired Industry Executive (Apple, IBM) Please let's get better introduced (6 questions) Ask my AI: https://answersfrom.me/jimtwin Regular mail: Jim Spohrer, ISSIP #431, 3561 Homestead Rd, Santa Clara, CA 95051 spohrer@gmail.com, 1-408-829-3112 https://www.linkedin.com/in/spohrer/ --- 20251031 Enterprise Platforms – Service Science & AI Perspectives October 31, 2025, 3:00pm PT at SJSU For Ammar Rayes(ISSIP, SJSU) Ammar’s LinkedIn Post: https://www.linkedin.com/posts/ammarrayes_it-was-a-great-honor-to-have-jim-spohrer-activity-7390239620371795968-4Tbd Revised Presentation (after discussion with Ammar and his SJSU MS Engineering students); Original Presentation: https://www.slideshare.net/slideshow/enterprise-platforms-sjsu-for-ammar_rayes-202510-v18-pptx/284000567 Ammar Rayes: https://www.linkedin.com/in/ammarrayes/ Jim Spohrer: https://www.linkedin.com/in/spohrer/ ---- 20250812 BayCHI Tuesday August 12, 2025, 7:30pm-9:00pm PT at UCSC-SV Santa Clara, CA For Ted Selker (https://www.linkedin.com/in/ted-selker/) Jim Spohrer ( https://www.linkedin.com/in/spohrer/) Presentation URL: https://www.slideshare.net/slideshow/202450812-baychi-ucsc-sv-20250812-v17-pptx/282395793 Recording: https://youtu.be/i43Q1-NjlCw Here are some links to the JimTwin adventure.... Real-time chatbot: Ask my AI (tmpt.me platform): https://answersfrom.me/jimtwin Not-yet-realtime avatar -> video: Jim Twin V1 (English video - HeyGen.ai platform) - https://youtu.be/T4S0uZp1SHw Jim Twin V1 (French video) - https://youtu.be/02hCGRJnCoc Jim Twin OpenSource (English video - Arnay Bhatia GitHub) – https://youtu.be/mwnZjTNegXE Jim Twin Tmpt.me Platform – https://tmpt.app/@jimtwin Writings & Recorded Talk: Jim Blog Post - https://service-science.info/archives/6612 Jim EIT Article (Real Jim) - https://www.eitdigital.eu/newsroom/grow-digital-insights/personal-ai-digital-twins-the-future-of-human-interaction/ Jim EIT Talk (Real Jim) - https://youtu.be/_1X6bRfOqc4 More about student(s) building JimTwin: HeyGen - Spring 2024 ISSIP AICollab Teams: https://issip.org/2024-collab-ai_digital_twins/ GitHub - Summer 2024 & 2025 Open Sourcewith Arnay Bhatia: https://youtu.be/QR17aXYgefk Inspiration from LinkedIn Founder... Reid Hoffman (English video - August 2024) - https://youtu.be/rgD2gmwCS10 .... as well as also from SJSU President: Cynthia Teniente Matson (English blog with video - May 21, 2025) - https://blogs.sjsu.edu/newsroom/2025/deep-dive-in-five-with-sjsu-president-cynthia-teniente-matson-introducing-the-new-presidential-ai-avatar/ URL: https://youtu.be/gqrIMItHyz8 Tonight I give a talk about the work at the ACM  BayCHI meeting URL: https://baychi.org/calendar/20250812/ Hope to have JimTwin avatar open-source working (near) real-time by my 70th birthday in Jan 2026 - to give talks in any language on my behalf based on my papers.
  • #3 URL: https://www.thriftbooks.com/w/cyberiada_stanisaw-lem/308647/item/86678184/
  • #4 BiblioA2024 Arbesman S (2025) The Magic of Code: How Digital Language Created and Connects Our World―and Shapes Our Future. URL: https://www.amazon.com/Magic-Code-Language-Connects-World_and/dp/1541704487 Quotes: " Chapter 8: Tools for Thought: Software for Thinking. Too often technology is at odds with humanity... For example... QWERTY... ... we have, by and large, adapted ourselves to technology in ways that are not good for us. Our increased drive for optimization of work can run directly counter to our ability to think deeply, or even feel human. "; Sam Arbesman on the magic of code, tools for thought, interdisciplinary ideas, and latent spaces (AC Ep5) URL: https://humansplus.ai/podcast/sam-arbesman-magic-code-tools-thought-interdisciplinary-ideas-latent-spaces-ac-ep5/
  • #5 BiblioD2025 Deming J & Hamel M (2025) Blueprint for a Spacefaring Civilization: The Science of Volition (By John Deming, with Mike Hamel) URL: https://www.amazon.com/Blueprint-Spacefaring-Civilization-Science-Volition/dp/B0DV4HB4R5 Quotes: "Cultural evolution is open-ended, yet, like physical and biological evolution, it is subject to underlying universal constraints. Once we understand those constraints, we can apply them to induce cultural evolution that becomes stabilized and impervious to systemic failure."; About John Deming URL: https://www.linkedin.com/in/john-deming-53258311/ About his daughter crying URL: https://youtu.be/H-UfesmmNdE About his daughter Laura Deming URL: https://en.wikipedia.org/wiki/Laura_Deming About Mike Hamel URL: https://www.linkedin.com/in/mikehamel/ The extreme libertarian view ("The Science of Volition") says pursue your individual personal happiness, and do your best to "do no harm" along the way; be as cooperative as you can with others. Increase benefits, decrease harms. Sounds simple enough - but why does it usually lead to crazy billionaires who disconnect from the rest from what seems like a lack of empathy (???). I also read this somewhat cynical comment this morning (Deming (2025) "Blueprint for Spacefaring Civilization", p. 106):. 10. “None of the really bright people I knew in college went into politics. They all sensed that, in terms of making a change in the world, politics wasn’t the place to be in the late Sixties and Seventies. All of them are in business now, which is funny, because they were the same people who trekked off to India or who tried in one way or another to find some sort of truth about life.” URL: https://www.leadquizzes.com/blog/steve-job-quotes/
  • #8 Jim Answers: Q1: WikiWork – open-source editable website based on O*NET (the jobs-tasks, occupations, careers, aspirations, hobbies, retiree roles) Q2: Turn my papers into talks in different language with 3 standard questions and 3 standard answers Q3: Follow 30 influencer experts for 2 hours a dady
  • #9 How does Jim suggest keeping up with accelerating change? Comment Jim suggère-t-il de suivre le rythme des changements accélérés ? JimTwin Jim suggère que pour suivre l'accélération du changement, il faut suivre ceux qui suivent les tendances et partagent leurs idées. Il souligne l'importance de l'apprentissage social comme super-pouvoir humain, qui peut être renforcé par l'IA. Jim conseille de créer un cadre personnel pour maintenir une perspective équilibrée sur le changement, en utilisant des dimensions pertinentes pour sa propre vie et ses centres d'intérêt. Il souligne également le rôle de l'IA et des technologies, comme les smartphones, pour aider les individus à rester connectés et informés. De plus, Jim souligne que l'IA continuera d'influencer le marché du travail et le rythme du changement, ce qui rend cruciale l'adaptation aux nouvelles technologies. Globalement, rester ouvert à l'apprentissage et être au courant des avancées technologiques sont des stratégies clés pour gérer efficacement le changement. French: English: Jim suggests that keeping up with accelerating change involves following people who track trends and share insights. He emphasizes the importance of social learning as a human super-power, which can be enhanced by AI. Jim advises creating a personal framework to maintain a balanced perspective on change, using dimensions that are relevant to one's own life and interests. He also highlights the role of AI and technology, such as smartphones, in helping individuals stay connected and informed. Additionally, Jim points out that AI will continue to impact the job market and the pace of change, making it crucial to adapt to new technologies. Overall, staying open to learning and being aware of technological advancements are key strategies for navigating change effectively. JimReal: French: La meilleure façon pour moi de suivre l'accélération du changement est d'apprendre des autres. Je suis des influenceurs et je les associe à deux dimensions : optimistes et réalistes, et acteurs et connaisseurs. Il est important de suivre des influenceurs diversifiés, aux opinions variées. English: The best way that I have found to keep up with accelerating change is to learn from others. I follow influencers, and plot their faces on two dimensions optimists-and-realists and doers-and-knowers. It is important to follow diverse influencers with a range of views. ===== Others Reid Hoffman - https://www.linkedin.com/in/reidhoffman/ Lukasz_Kaiser - https://www.linkedin.com/in/lukaszkaiser/ AnatasiInTech - https://www.youtube.com/@AnastasiInTech AI Explained - https://www.youtube.com/@aiexplained-official Ross_Dawson - https://www.linkedin.com/in/futuristkeynotespeaker/ Andrew Ng - https://www.linkedin.com/in/andrewyng/ Higher Bar – avoid the hype and understand potential harms Substack: Arvind Narayanan & Sayash Kapoor - AI Snake Oil (Princeton) Substack: Gary Markus (NYU) Facebook: Ernest Davis (NYU) LinkedIn & Twitter: Stephen Wolfram Blog: Irving Wladawsky-Berger (MIT, retired IBM) Practical AI Upskilling Advice – benefits, which prompts to explore and why? Substack: Ethan Mollick (U Penn Wharton) Tracking AI Capabilities – (FOMO) which tools to try? The Neuron Daily (email AI newsletter - Purrfect): Noah Edelman & Pete Huang LinkedIn & Website: Terri Griffith (Simon Frasier) YouTube: AI Explained ArXiv publications from Google, Deepmind, Microsoft, OpenAI, Facebook/Meta, IBM, etc. Website: PapersWithCode/SOTA (and GiTHub – tracking stars on projects) Broader topics and implications (overly optimistic?) YouTube: Alan D. Thomas (Australia) (super optimistic) See his interview with Harvey Castro MD (here) – also books, and visionary uses for personalized medicine (personalized communications) YouTube: Lex Friedman (MIT) (super knowledgeable guests interviewed) Substack: Lee Nackman (retired IBM) (Win-Win Democracy and AI topics – balanced – well researched) YouTube: Kartik Gada (The ATOM) – accelerating change [accelerating change perspective – details beyond Kurzweil & Altman) Substack – Ethan Mollick: https://oneusefulthing.substack.com/p/using-ai-to-make-teaching-easier Email – The Neuron Daily – Noah Edelman & Pete Huang https://www.theneurondaily.com/p/ai-deepfakes BiblioN2023 Narayanan A, Kapoor S (2023) Evaluating LLMs is a minefield: Annotated slides from a recent talk. Sayash and Arvind from AI Snake Oil <aisnakeoil@substack.com> Wed, Oct 4, 2023 at 7:40 AM. ARVIND NARAYANAN AND SAYASH KAPOOR. OCT 4 Via_Substack. URL: https://www.aisnakeoil.com/p/evaluating-llms-is-a-minefield Quotes: "We have released annotated slides for a talk titled Evaluating LLMs is a minefield. We show that current ways of evaluating chatbots and large language models don't work well, especially for questions about their societal impact. There are no quick fixes, and research is needed to improve evaluation methods."; BiblioM2023 Marcus G (2023) Seven Lies in Four Sentences. Gary Marcus on AI. Via_Substack. URL: https://garymarcus.substack.com/p/seven-lies-in-four-sentencesQuotes: "Earlier today I learned that 2 billion people are eligible to vote in elections in 2024, in scores of elections around the globe. Tyler Cowen tried to argue yesterday in his Bloomberg column that misinformation doesn’t matter. Anybody remember Brexit?"; BiblioT2023 Thompson AD (2023) AI + medicine - with Harvey Castro MD (GPT-4, Med-PaLM 2, Carbon Health, Ambience, 311 ChatGPT call). Via_Harvey_Casto. URL: https://youtu.be/jTmkiGjrgpA Quotes: "14,365 views Jul 5, 2023 The Memo: https://lifearchitect.ai/memo/ Annotated Med-Palm 2 paper: https://lifearchitect.ai/report-card/ Harvey: https://www.harveycastromd.info/ https://www.amazon.com/stores/Harvey-... https://www.linkedin.com/in/harveycas... https://twitter.com/harveycastromd https://www.instagram.com/harveycastr... 00:00 Start! 07:23 AI by age 12:17 The Gap 14:47 Models (ChatGPT, GPT-4, Med-PaLM 2) 23:26 Use cases including non-emergency calls 35:28 Medicine vs self-driving cars 46:56 Harvey's favorite AI use case 52:56 AI as a medical partner Dr Alan D. Thompson is a world expert in artificial intelligence (AI), specialising in the augmentation of human intelligence, and advancing the evolution of ‘integrated AI’. Alan’s applied AI research and visualisations are featured across major international media, including citations in the University of Oxford’s debate on AI Ethics in December 2021. https://lifearchitect.ai/ ";
  • #10 URL: http://fasterthan20.com/ URL: https://xkcd.com/1232/
  • #11 . Past: Which of the following are important facts to remember in the history of semiconductors that enable today's AI systems? a. 1947 Transistor (Bell Labs) b. 1958 Integrated Circuit (Texas Instruments) c. 1971 Microprocessor (Intel) d. All of the above 2. Present: Which of the following are important facts about H100 chip units in today's AI in data centers? a. weight: 70 pounds b. complexity: 35,000 parts c. cost: 250,000 dollars d. All of the above 3. Future: Which of the following are important capabilities to understand to be prepared for life in the future? a. AI Digital Twins of People, to keep up with accelerating change b. Humanoid Robots, to accelerate the local sustainable economy trend c. Self-Control, to maintain healthy decision making d. All of the above
  • #12 To: Marco Podien <marco.podien@gmail.com>, Jim Spohrer <spohrer@gmail.com> Questions by November 24th to EIT Staff Asja Kamenica <asja.kamenica@eitdigital.eu> Andrea Lorenzin <andrea.lorenzin@eitdigital.eu> Q: How many of you have tries generative AI? a. Q: In what year was the first AI workshop? a. 1917, b. 1956, c. 1968, d. 1997 A: b. 1956 Q: In what year did ChatGPT attain 100B users after just two months? a. 2021, b. 2022, c. 2023, d. 2024 A: c. 2023 Q: In what year (approximate decade) is it predicted that an exascale (~one human brain) of computation will cost $1000? a. 2030, b. 2040, c. 2050, d. 2060 A: d. 2060 Q: In what year (approximate decade) is it predicted that a ronnascale (~billion human brains) of computation will cost $1B? a. 2080, b. 2100, c. 2200, d. Never A: a. 2080
  • #13 URL: https://www.youtube.com/watch?v=cEg8cOx7UZk
  • #14 Here is the explanation that kids and everyone I spoke with understands. Explaining Generative AI to Nearly Anyone Have you ever used a calculator to add up numbers?  Generative AI is like a calculator - you ask it to please do something - and you will always get an answer, usually pretty quickly. However, depending on the question you ask, the answer is only correct one day a week.. Four days a week the answer is not correct, but made up - and may sound very creative or very convincing. Two days a week, the calculator says - sorry I cannot help you - again, depending on what you ask the calculator to do. What would you do with a calculator like this - only giving a correct answer some of the time? Some people would throw it away. However, some people are very happy to use it to make-up creative answers to hard questions - even if it only helps them some of the time. Especially for pictures, stories, poems, and  art work, like this one picture of a monkey and a parrot - some people find these kind of calculators helpful.  I asked a generative AI calculator to do something for me once - I asked for a picture, and asked in this funny way: "Please create an image of a library, and in the library is monkey using a typewriter with a stochastic parrot dictating to the monkey." It made a pretty funny picture,  wouldn't you say? Also, generative AI calculators are good at making up answers very, very fast... ...and sometimes they are right, but most of the time they are either creatively wrong or don't give an answer. Sadly, some people think the calculator is really smart - because it can give a correct answer to a hard question, some of the time - and do it really, really fast. The calculator has fooled them into thinking it is really, really smart - when in fact, it is not smart.  If it was smart, it would not make so many mistakes. So that works most of the time. However, if they do not know what a calculator is - I was talking with a 3 year the other day whose parent works for tech company in Silicon Valley, and had asked me to explain AI to his daughter - I basically just substitute "a magic genie" for the calculator, and talk about a genie who gives you your wishes, but makes a lot of mistakes - so you have to be careful what you wish for. To explain why it is "so good" sometimes, I have to explain N-Gram Statistics - which is a bit harder, but if they do not understand N-grams, I just say: How does the generative AI calculator work? Use your imagination to imagine a computer keyboard/or typewriter  that had whole words and whole sentences on millions of keys, so when you push a key at random, you get something that makes sense. The more examples you show this magic keyboard over time, the more keys the keyboard gets - billions or even trillions of keys, and the better the keyboard gets at putting a big key in the middle that says "PUSH ME NEXT PLEASE". Using this magic keyboard/typewriter even a monkey or a parrot could sometimes create pretty amazing things. Inside a computer words, pictures, videos are just represented as 0’s and 1’s – as big big numbers. To understand this we can play the game called 20 questions, which can be used to identify anything by asking enough yes and no questions. Are you thinking about an animal? Yes or No? Yes, Does the animal have a furry tale? Yes, Does the animal like to ear bananas? Yes. Is the animal a monkey? Not sure if this is helpful, but thought I would share it.
  • #15 What is really going on in this progress? Starting at the 2017 paper introducing the transformer architecture. The big insights are once you have a general purpose learning architecture (with enough scale), you can then get by with a transformer architecture (attention heads as working memory to predict what comes next) – as you get better at predicting what comes next (with enough scale), you being to see emergence (the ability to get new-ish capabilities) by appropriate prompt engineering (few-shot learning) – his happens where the scale model has developed a good compressed version of some pattern of reality that is a good predictor. Getting these compressed models of reality that are good predictors under certain conditions is both an efficiency and a trap. Efficiency is the world is stable. Trap is the world is changing rapidly, and the compressed version is no longer valid. Predicting what comes next is a kind of un-supervised learning – what comes next is a property of the data/world and does not require labeling. Once you have the predictor working well, and the compressed models of the data/world working well, then the emergence happens for newish-capabilities few-shot learning with appropriate prompts. This is like learning by being told. It has to be rewarded as many times as possible, when it makes use of the ”value statements in the constitution” – reinforncing the in-group bias. Because LLMs have all the data (lots and lots of data) from different groups with difference values/biases/belief systems, it is important to get the addition of a constitution and lots of rewards, or else …. Or else, bad behaviour, hallucinations, and other strange phenomena will occur. Is this where schizophrenia comes from in people? A clash of belief systems, and what should get rewarded. Looking for truth, but without the flexibility to adapth. Without the anchor principles that can make life a peaceful journey. Perhaps. 2020 – Few shot learners implies emergence. Emergence just means ”good enough compressed models of reality/diverse data at scale” that a short prompt can bias the prediction of what comes next. 2022 – Constitutional AI implies value systems/belief systems matter for socially acceptable behavior. A learner must be conditioned/repeatedly rewarded for pro-social behaviors. DALL-E URL: https://openai.com/product/dall-e-2 ChatGPT URL: https://chat.openai.com GPT-4 URL: https://openai.com/research/gpt-4 AlphaFold: URL https://en.wikipedia.org/wiki/AlphaFold Microsoft Bing: URL: https://en.wikipedia.org/wiki/Microsoft_Bing URL: https://en.wikipedia.org/wiki/History_of_artificial_intelligence URL: http://www.businessinsider.com/infographic-ai-effect-on-economy-2017-8 Today’s infographic comes from the Extraordinary Future 2017, a new conference in Vancouver, BC that focuses on emerging technologies such as AI, autonomous vehicles, fintech, and block http://extraordinaryfuture.com/e/extraordinary-future-2017-71chain tech. Nathaniel Rochester: In 1948, Rochester moved to IBM where he designed the IBM 701, the first general purpose, mass-produced computer. He wrote the first symbolic assembler, which allowed programs to be written in short, readable commands rather than pure numbers or punch codes. BiblioV2017 Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, Illia Polosukhin (2017) Attention Is All You Need. URL: https://arxiv.org/abs/1706.03762v5 Quotes: "The dominant sequence transduction models are based on complex recurrent or convolutional neural networks in an encoder-decoder configuration. The best performing models also connect the encoder and decoder through an attention mechanism. We propose a new simple network architecture, the Transformer, based solely on attention mechanisms, dispensing with recurrence and convolutions entirely. Experiments on two machine translation tasks show these models to be superior in quality while being more parallelizable and requiring significantly less time to train. Our model achieves 28.4 BLEU on the WMT 2014 English-to-German translation task, improving over the existing best results, including ensembles by over 2 BLEU. On the WMT 2014 English-to-French translation task, our model establishes a new single-model state-of-the-art BLEU score of 41.8 after training for 3.5 days on eight GPUs, a small fraction of the training costs of the best models from the literature. We show that the Transformer generalizes well to other tasks by applying it successfully to English constituency parsing both with large and limited training data."; BiblioB2020 Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, Dario Amodei (2020) Language Models are Few-Shot Learners. URL: https://arxiv.org/abs/2005.14165v4 Quotes: "Recent work has demonstrated substantial gains on many NLP tasks and benchmarks by pre-training on a large corpus of text followed by fine-tuning on a specific task. While typically task-agnostic in architecture, this method still requires task-specific fine-tuning datasets of thousands or tens of thousands of examples. By contrast, humans can generally perform a new language task from only a few examples or from simple instructions - something which current NLP systems still largely struggle to do. Here we show that scaling up language models greatly improves task-agnostic, few-shot performance, sometimes even reaching competitiveness with prior state-of-the-art fine-tuning approaches. Specifically, we train GPT-3, an autoregressive language model with 175 billion parameters, 10x more than any previous non-sparse language model, and test its performance in the few-shot setting. For all tasks, GPT-3 is applied without any gradient updates or fine-tuning, with tasks and few-shot demonstrations specified purely via text interaction with the model. GPT-3 achieves strong performance on many NLP datasets, including translation, question-answering, and cloze tasks, as well as several tasks that require on-the-fly reasoning or domain adaptation, such as unscrambling words, using a novel word in a sentence, or performing 3-digit arithmetic. At the same time, we also identify some datasets where GPT-3's few-shot learning still struggles, as well as some datasets where GPT-3 faces methodological issues related to training on large web corpora. Finally, we find that GPT-3 can generate samples of news articles which human evaluators have difficulty distinguishing from articles written by humans. We discuss broader societal impacts of this finding and of GPT-3 in general."; BiblioB2022 Yuntao Bai, Saurav Kadavath, Sandipan Kundu, Amanda Askell, Jackson Kernion, Andy Jones, Anna Chen, Anna Goldie, Azalia Mirhoseini, Cameron McKinnon, Carol Chen, Catherine Olsson, Christopher Olah, Danny Hernandez, Dawn Drain, Deep Ganguli, Dustin Li, Eli Tran-Johnson, Ethan Perez, Jamie Kerr, Jared Mueller, Jeffrey Ladish, Joshua Landau, Kamal Ndousse, Kamile Lukosuite, Liane Lovitt, Michael Sellitto, Nelson Elhage, Nicholas Schiefer, Noemi Mercado, Nova DasSarma, Robert Lasenby, Robin Larson, Sam Ringer, Scott Johnston, Shauna Kravec, Sheer El Showk, Stanislav Fort, Tamera Lanham, Timothy Telleen-Lawton, Tom Conerly, Tom Henighan, Tristan Hume, Samuel R. Bowman, Zac Hatfield-Dodds, Ben Mann, Dario Amodei, Nicholas Joseph, Sam McCandlish, Tom Brown, Jared Kaplan (2022) Constitutional AI: Harmlessness from AI Feedback URL: https://arxiv.org/abs/2212.08073 Quotes: "As AI systems become more capable, we would like to enlist their help to supervise other AIs. We experiment with methods for training a harmless AI assistant through self-improvement, without any human labels identifying harmful outputs. The only human oversight is provided through a list of rules or principles, and so we refer to the method as 'Constitutional AI'. The process involves both a supervised learning and a reinforcement learning phase. In the supervised phase we sample from an initial model, then generate self-critiques and revisions, and then finetune the original model on revised responses. In the RL phase, we sample from the finetuned model, use a model to evaluate which of the two samples is better, and then train a preference model from this dataset of AI preferences. We then train with RL using the preference model as the reward signal, i.e. we use 'RL from AI Feedback' (RLAIF). As a result we are able to train a harmless but non-evasive AI assistant that engages with harmful queries by explaining its objections to them. Both the SL and RL methods can leverage chain-of-thought style reasoning to improve the human-judged performance and transparency of AI decision making. These methods make it possible to control AI behavior more precisely and with far fewer human labels.";
  • #16 URL: http://www-formal.stanford.edu/jmc/history/dartmouth/dartmouth.html URL: https://en.wikipedia.org/wiki/Nathaniel_Rochester_(computer_scientist) BiblioM1955 McCarthy J, Minsky ML, Rochester N, Shannon CE (1955) A proposal for a summer workshop on Artificial Intelligence. URL: http://jmc.stanford.edu/articles/dartmouth/dartmouth.pdf Quotes: "We propose that a 2 month, 10 man study of artificial intelligence be carried out during the summer of 1956 at Dartmouth College in Hanover, New Hampshire. The study is to proceed on the basis of the conjecture that every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it. An attempt will be made to find how to make machines use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves. We think that a significant advance can be made in one or more of these problems if a carefully selected group of scientists work on it together for a summer. The following are some aspects of the artificial intelligence problem: (1) Automatic Computers, (2) How Can a Computer be Programmed to Use a Language, (3) Neuron Nets, (4) Theory of the Size of a Calculation, (5) Self_Improvement, (6) Abstraction, (7) Randomness and Creativity, (8) "; "Estimated Expenses 6 salaries of 1200 - $7200 2 salaries of 700 - 1400 8 traveling and rent expenses averaging - 2400 Secretarial and organizational expense - 850 Additional traveling expenses - 600 Contingencies - 550 Total - $13,500"; BiblioO2023 OpenAI (2023) GPT-4 Technical Report. Via_OpenAI_SM_JCS. URL: https://cdn.openai.com/papers/gpt-4.pdf Quotes: "Abstract - We report the development of GPT-4, a large-scale, multimodal model which can accept image and text inputs and produce text outputs. While less capable than humans in many real-world scenarios, GPT-4 exhibits human-level performance on various professional and academic benchmarks, including passing a simulated bar exam with a score around the top 10% of test takers. GPT-4 is a Transformer- based model pre-trained to predict the next token in a document. The post-training alignment process results in improved performance on measures of factuality and adherence to desired behavior. A core component of this project was developing infrastructure and optimization methods that behave predictably across a wide range of scales. This allowed us to accurately predict some aspects of GPT-4’s performance based on models trained with no more than 1/1,000th the compute of GPT-4.";
  • #21 BiblioR2018 Rouse WB, Spohrer JC (2018) Automating versus augmenting intelligence. Journal of Enterprise Transformation, 8:1-2, 1-21, DOI: 10.1080/19488289.2018.1424059. URL: https://service-science.info/wp-content/uploads/2018/08/Rouse-Spohrer-Automating-Versus-Augmenting-Intelligence-12-21-17-copy.pdf Quotes: "Abstract: This article addresses the prospects for automating intelligence versus augmenting human intelligence. The evolution of artificial intelligence (AI) is summarized, including contemporary AI and the new capabilities now possible. Functional requirements to augment human intelligence are outlined. An overall architecture is presented for providing this functionality, including how it will make deep learning explainable to decision makers. Three case studies are addressed, including driverless cars, medical diagnosis, and insurance underwriting. Paths to transformation in these domains are discussed. Prospects for innovation are considered in terms of what we can now do, what we surely will be able to do soon, and what we are unlikely to ever be able to do."; BiblioS2017 Imagination Challenge: Quantify and graph cost of digital workers and GDP per employee USA from 1960-2080. Service-Science.Info Blog Post. URL: https://service-science.info/archives/4741 Quotes: "Imagination challenge: Consider quantifying and graphing the decreasing cost of digital workers due to Moore’s Law, and increasing GDP/Employees USA from 1960 to 2080 (projected). A narrow digital worker will cost about a million dollars by 2025, and require a petascale computational system. The same digital worker will cost about a thousand dollars by 2045, and about $1 by 2065."; If you are an entrepreneur or CEO you are excited about the drop in cost of digital workers, because that means GDP per employee will continue its exponential increase. Source: http://service-science.info/archives/4741
  • #22 To understand in part why this is so, take a look at the fastest super-computer in the world… IBM helped build it for Oakridge National Labs, and it can do 200 million billion instructiosn per second using 13 Megawatts of power.
  • #23 Compate that to the human brain which can by many estimates perform a billion billion instructions per second (5x more than Summit) on a mere 20 watts, over 100,000 times less power.
  • #24 What does Jim see as the driving force in future service offerings in business and government? Selon Jim, quelle est la force motrice des futures offres de services dans les entreprises et au sein du gouvernement ? JimTwin French: Jim Spohrer identifie la technologie, et plus particulièrement le numérique et l'intelligence artificielle (IA), comme un moteur majeur de l'avenir des services offerts aux entreprises et aux administrations publiques. Il souligne comment la technologie a historiquement transformé les entreprises et la société, chaque génération bénéficiant de nouvelles avancées qui amplifient les capacités individuelles et organisationnelles. Internet, le World Wide Web et les smartphones ont déjà multiplié les services technologiques, et l'IA est considérée comme la ressource la plus récente pouvant être mise au service d'autrui. Jim souligne également que la pandémie a accéléré la transformation numérique, transformant les expériences de service quotidiennes. Cette transformation ne se limite pas aux avancées technologiques, mais s'adapte également aux nouveaux modes d'interaction et de prestation de services. L'accent mis sur la transformation numérique et l'IA suggère une évolution vers des offres de services plus efficaces, évolutives et personnalisées, tant dans les entreprises que dans les administrations publiques. Globalement, l'intégration de l'IA et des technologies numériques devrait continuer à stimuler l'innovation et l'efficacité des systèmes de services, permettant des applications plus complexes des ressources pour répondre aux besoins des individus et des organisations. English: Jim Spohrer identifies technology, particularly digital and artificial intelligence (AI), as a significant driving force in the future of service offerings in business and government. He highlights how technology has historically transformed business and society, with each generation experiencing new advancements that amplify individual and organizational capabilities. The Internet, World Wide Web, and smartphones have already increased technology-mediated services, and AI is seen as the latest resource that can be applied to benefit others. Jim also notes that the pandemic has accelerated digital transformation, leading to changes in daily service experiences. This transformation is not only about technological advancements but also about adapting to new ways of interacting and delivering services. The focus on digital transformation and AI suggests a shift towards more efficient, scalable, and personalized service offerings in both business and government sectors. Overall, the integration of AI and digital technologies is expected to continue driving innovation and efficiency in service systems, enabling more complex applications of resources to meet the needs of individuals and organizations. JimReal: French: Le moteur de l'avenir des services réside dans la disparition du coût marginal de calcul. Tout a un coût : l'énergie, les matériaux, la main-d'œuvre et, de plus en plus, un coût de calcul. À mesure que le coût de calcul se rapproche de zéro, la productivité des travailleurs du savoir ne cessera de croître. Les gens ne seront plus seulement des entrepreneurs en série, mais des entrepreneurs parallèles. Nous devons donc aider la prochaine génération à se fixer des objectifs plus ambitieux, des objectifs qui comptent vraiment, car chacun d'entre eux aura plus de 100 travailleurs numériques à son service. Cette image est ma version de la loi de Moore : la puissance de calcul estimée d'un cerveau humain est de l'ordre de l'exascale, soit un milliard de milliards d'instructions par seconde. On estime que ce coût ne sera que de 1 000 dollars d'ici 2060. English: The driving force in the future of service is the marginal cost of computing going to zero. Everything has costs - energy, materials, labor, and yes increasingly a computational cost. As the cost of computation gets closer and closer to zero, knowledge worker productivity will go up and up. People will not just serial entrepreneurs, but parallel entrepreneurs. So we need to help the next generation learn to set bigger goals, goals that really matter, because each of them will have more than a 100 digital workers working for them. This picture is my version of Moore's law, and the estimated computing power of one human brain is an exascale - a billion billion instructions per second. It is estimate that cost will be just $1000 by 2060. ===== BiblioR2018 Rouse WB, Spohrer JC (2018) Automating versus augmenting intelligence. Journal of Enterprise Transformation, 8:1-2, 1-21, DOI: 10.1080/19488289.2018.1424059. URL: https://service-science.info/wp-content/uploads/2018/08/Rouse-Spohrer-Automating-Versus-Augmenting-Intelligence-12-21-17-copy.pdf Quotes: "Abstract: This article addresses the prospects for automating intelligence versus augmenting human intelligence. The evolution of artificial intelligence (AI) is summarized, including contemporary AI and the new capabilities now possible. Functional requirements to augment human intelligence are outlined. An overall architecture is presented for providing this functionality, including how it will make deep learning explainable to decision makers. Three case studies are addressed, including driverless cars, medical diagnosis, and insurance underwriting. Paths to transformation in these domains are discussed. Prospects for innovation are considered in terms of what we can now do, what we surely will be able to do soon, and what we are unlikely to ever be able to do."; BiblioS2017 Imagination Challenge: Quantify and graph cost of digital workers and GDP per employee USA from 1960-2080. Service-Science.Info Blog Post. URL: https://service-science.info/archives/4741 Quotes: "Imagination challenge: Consider quantifying and graphing the decreasing cost of digital workers due to Moore’s Law, and increasing GDP/Employees USA from 1960 to 2080 (projected). A narrow digital worker will cost about a million dollars by 2025, and require a petascale computational system. The same digital worker will cost about a thousand dollars by 2045, and about $1 by 2065."; If you are an entrepreneur or CEO you are excited about the drop in cost of digital workers, because that means GDP per employee will continue its exponential increase. Source: http://service-science.info/archives/4741
  • #25 BiblioR2018 Rouse WB, Spohrer JC (2018) Automating versus augmenting intelligence. Journal of Enterprise Transformation, 8:1-2, 1-21, DOI: 10.1080/19488289.2018.1424059. URL: https://service-science.info/wp-content/uploads/2018/08/Rouse-Spohrer-Automating-Versus-Augmenting-Intelligence-12-21-17-copy.pdf Quotes: "Abstract: This article addresses the prospects for automating intelligence versus augmenting human intelligence. The evolution of artificial intelligence (AI) is summarized, including contemporary AI and the new capabilities now possible. Functional requirements to augment human intelligence are outlined. An overall architecture is presented for providing this functionality, including how it will make deep learning explainable to decision makers. Three case studies are addressed, including driverless cars, medical diagnosis, and insurance underwriting. Paths to transformation in these domains are discussed. Prospects for innovation are considered in terms of what we can now do, what we surely will be able to do soon, and what we are unlikely to ever be able to do."; BiblioS2017 Imagination Challenge: Quantify and graph cost of digital workers and GDP per employee USA from 1960-2080. Service-Science.Info Blog Post. URL: https://service-science.info/archives/4741 Quotes: "Imagination challenge: Consider quantifying and graphing the decreasing cost of digital workers due to Moore’s Law, and increasing GDP/Employees USA from 1960 to 2080 (projected). A narrow digital worker will cost about a million dollars by 2025, and require a petascale computational system. The same digital worker will cost about a thousand dollars by 2045, and about $1 by 2065."; If you are an entrepreneur or CEO you are excited about the drop in cost of digital workers, because that means GDP per employee will continue its exponential increase. Source: http://service-science.info/archives/4741
  • #26 Translate this into French as a possible introduction Paul would give to Jim Spohrer and digital twins… Reid Hoffman meets his AI twin - URL: https://youtu.be/rgD2gmwCS10
  • #27 URL:  https://blogs.sjsu.edu/newsroom/2025/deep-dive-in-five-with-sjsu-president-cynthia-teniente-matson-introducing-the-new-presidential-ai-avatar/
  • #28 Here are some links to the JimTwin adventure.... Real-time chatbot: Ask my AI (tmpt.me platform): https://answersfrom.me/jimtwin Not-yet-realtime avatar -> video: Jim Twin V1 (English video - HeyGen.ai platform) - https://youtu.be/T4S0uZp1SHw Jim Twin V1 (French video) - https://youtu.be/02hCGRJnCoc Jim Twin OpenSource (English video - Arnay Bhatia GitHub) – https://youtu.be/mwnZjTNegXE Jim Twin Tmpt.me Platform – https://tmpt.app/@jimtwin Writings & Recorded Talk: Jim Blog Post - https://service-science.info/archives/6612 Jim EIT Article (Real Jim) - https://www.eitdigital.eu/newsroom/grow-digital-insights/personal-ai-digital-twins-the-future-of-human-interaction/ Jim EIT Talk (Real Jim) - https://youtu.be/_1X6bRfOqc4 More about student(s) building JimTwin: HeyGen - Spring 2024 ISSIP AICollab Teams: https://issip.org/2024-collab-ai_digital_twins/ GitHub - Summer 2024 & 2025 Open Sourcewith Arnay Bhatia: https://youtu.be/QR17aXYgefk Inspiration from LinkedIn Founder... Reid Hoffman (English video - August 2024) - https://youtu.be/rgD2gmwCS10 .... as well as also from SJSU President: Cynthia Teniente Matson (English blog with video - May 21, 2025) - https://blogs.sjsu.edu/newsroom/2025/deep-dive-in-five-with-sjsu-president-cynthia-teniente-matson-introducing-the-new-presidential-ai-avatar/ URL: https://youtu.be/gqrIMItHyz8 Tonight I give a talk about the work at the ACM  BayCHI meeting URL: https://baychi.org/calendar/20250812/ Hope to have JimTwin avatar open-source working (near) real-time by my 70th birthday in Jan 2026 - to give talks in any language on my behalf based on my papers.
  • #29 https://www.bing.com/images/create/create-a-historical-progression-in-four-parts-from/1-67d9868f21fc4f58b7dafbfa9a07733b?id=i3SylcH3p1nnBAUKQ%2fK43Q%3d%3d&view=detailv2&idpp=genimg&thId=OIG3.tmmO_0baNjubIgucstRz&skey=4SDGLQ9GyoHHAuA0LSMnQmlxDg4D74CFHBBI9SPbzJ0&FORM=GCRIDP&ajaxhist=0&ajaxserp=0 Hall & Boccanfuso (forthcoming) University Industry Collaboration: Innovation at the Interface. Springer. Spohrer, J.C. (2010). IBM's University Programs. IEEE Computer 43(8):102-104. URL: https://service-science.info/wp-content/uploads/2017/04/IBM-GUP-5Rs-copy-2.pdf Spohrer, J.C. (2013). What's Up at IBM? University Programs! The 6 R's helping to build a Smarter Planet: Research, Readiness, Recruiting, Revenue, Responsibility, Regions. May 14, 2013. Slideshare. URL: https://www.slideshare.net/slideshow/ibm-up-external-20130514-v11/21175603 Spohrer, J. (2017). IBM's service journey: A summary sketch. Industrial Marketing Management, 60, 167-172. URL: https://www.sciencedirect.com/science/article/abs/pii/S0019850116301778?via%3Dihub Spohrer, J. (2024a). AI Upskilling and Digital Twins: A Service Science Perspective on the Industry 4.0 to Industry 5.0 Shift. In Industry 4.0 to Industry 5.0: Explorations in the Transition from a Techno-economic to a Socio-technical Future (pp. 79-92). Singapore: Springer Nature. URL: https://link.springer.com/chapter/10.1007/978-981-99-9730-5_4 Spohrer, J. (2024b) Personal AI digital twins: the future of human interaction? EIT Digital. URL: https://www.eitdigital.eu/newsroom/grow-digital-insights/personal-ai-digital-twins-the-future-of-human-interaction/.
  • #30 3Es = Energy, Errors, Ethics Energy: “By 2030, AI data centers could take a bigger share of carbon emissions than flights do currently” ChartR from Axios from Accenture report URL: https://www.axios.com/2025/06/25/ai-emissions-accenture-study?utm_source=chartr&utm_medium=email&utm_campaign=chartr_20250627 Hallucinations = ”BS” = Confident Errors In people, we would call it ”BS” or “Delusional Lying” BiblioH2024 Hicks MT, Humphries J, Slater J (2024) ChatGPT is bullshit. Via_LinkedIn URL: https://link.springer.com/article/10.1007/s10676-024-09775-5 Quotes: "Hicks, M.T., Humphries, J. & Slater, J. ChatGPT is bullshit. Ethics Inf Technol 26, 38 (2024). https://doi.org/10.1007/s10676-024-09775-5"; Failure to Communicate - https://carpediemdona.com/2021/04/01/mondays-v2e16-failure-to-communicate/
  • #31 This is the best explanation Jim Spohrer can give on June 29, 2025. Perhaps I can improve this explanation over time as I find good YouTubes _1 Andrej Karpathy – latent spaces _2 Something.AI – low dimensional visualizations _3 Something – “black holes” of optimization surprise Deep Dive into LLMs like ChatGPT Andrej Karpathy 635K subscribers, 294K views 1 day ago This is a general audience deep dive into the Large Language Model (LLM) AI technology that powers ChatGPT and related products. URL: https://youtu.be/7xTGNNLPyMI Latent Space Visualisation: PCA, t-SNE, UMAP | Deep Learning Animated Deepia (25K subscribers, 92K views 10 months ago #Manim #somepi #PCA) In this video you will learn about three very common methods for data dimensionality reduction: PCA, t-SNE and UMAP. These are especially useful when you want to visualise the latent space of an autoencoder. URL: https://youtu.be/o_cAOa5fMhE --- "[LLM] never induce proper world[model]s of anything. Everything that they do is through mimicry." Two trends I see that may lead to proper world models from LLMs: (1) Deeper understanding of the mathematics of mapping between high and low dimensional latent spaces. For example, see:  URL: https://youtu.be/o_cAOa5fMhE People can turn low dimensional representations of datasets  into world models more easily than high dimensional representations. Herb Simon did work on this: URL: https://iiif.library.cmu.edu/file/Simon_box00061_fld04598_bdl0012_doc0002/Simon_box00061_fld04598_bdl0012_doc0002.pdf (2) LLMs generating Python programs as world models to generate synthetic datasets (I just started working on this) I am sure many others are working on this approach as well. ---
  • #32 URL: https://med.stanford.edu/news/all-news/2025/07/virtual-scientist.html
  • #34 Types: Progression of Models : Verified, Trusted, Wise Models = instruction set of future: Better building blocks Demirkan H, Spohrer J (2025) Talent Management: “Here Come the Digital Workers!”. In ORMS Today, INFORMS, June 17, 2025. URL: https://pubsonline.informs.org/do/10.1287/orms.2025.02.15/full/
  • #35 URL: https://naplesforumonservice.com/wp-content/uploads/2021/02/NFS2019-Barile-Piciocchi-Saviano-Bassano-Pietronudo-Spohrer.pdf BiblioB2019 Barile S, Piciocchi P, Saviano M, Bassano C, Pietronudo C, Spohrer JC (2019) Towards a new logic of value co-creation in the digital age: doing more and agreeing less. Naples Forum on Service. URL: https://naplesforumonservice.com/wp-content/uploads/2021/02/NFS2019-Barile-Piciocchi-Saviano-Bassano-Pietronudo-Spohrer.pdf
  • #36 1440 News (July 11, 2025) URL: https://link.join1440.com/view/66c4c70d5d78644b3abaeeb0o75d4.1n93p/59f6eb4c URL: https://www.usatoday.com/picture-gallery/entertainment/celebrities/2025/07/11/see-photos-of-jane-birkin/84540857007/ Original 'It' Bag The original Hermès Birkin bag sold yesterday at Sotheby’s Paris for approximately $10.1M, the most expensive handbag ever sold at auction. The black leather prototype, featuring actress Jane Birkin’s initials, a nondetachable strap, and gilded brass hardware, was purchased in under 20 minutes by a Japanese private collector.   The bag’s story began in the 1980s when the actress met Hermès CEO Jean-Louis Dumas on a flight. Frustrated with her handbag, Birkin described her ideal bag to Dumas, and they famously sketched the design on an airsickness bag. Today, the bag is a global symbol of exclusivity and wealth, with prices for new bags typically ranging from $10K to $60K and waitlists that can last years. Only select clients—often those who have spent thousands on prior purchases—are invited to buy.   Birkins are widely considered investment pieces, with some estimates showing an average annual value increase of 14.2%. Each bag is made by a single artisan and reportedly takes at least 18 hours to construct. \
  • #37 URL: https://link.springer.com/chapter/10.1007/978-981-99-9730-5_4 Covey’s 7 Habits – Sharpen The Saw - https://toggl.com/blog/begin-with-the-end-in-mind First…what are The 7 Habits of Highly Effective People? The 7 Habits of Highly Effective People, published in 2004, is a popular book by Stephen R. Covey. For the past 20+ years, it’s been a popular resource for anyone who wants to solve problems in their own life, whether professional or personal. Be proactive. Take responsibility for your actions instead of blaming external circumstances. You’re in charge of your own life and shape it by making conscious choices. The idea is to act first before being acted upon. Begin with the end in mind. Define a clear end goal to work toward so you live purposefully and prioritize actions that make a difference. Put first things first. Prioritize tasks based on importance instead of urgency. Carefully choose those tasks that align with your long-term goals. Think win-win. In relationships, look for situations where every party involved can benefit somehow. This fosters collaboration, trust, and shared success. Seek first to understand, then to be understood. Lead with empathy, igniting your active listening skills and thinking carefully before you respond. Synergize. As a team, you can achieve more than an individual. Sharpen the saw. Invest in becoming a better version of yourself physically, emotionally, mentally, and spiritually. Practice these habits day-to-day, as it’s the only way to stay resilient and continue growing.
  • #38 URL Amazon: https://www.amazon.com/Knowledge-Rebuild-Civilization-Aftermath-Cataclysm-ebook/dp/B00DMCV5YS/ URL TED Talk: https://www.youtube.com/watch?v=CdTzsbqQyhY Citation: Dartnell L (2012) The Knowledge: How to Rebuild Civilization in the Aftermath of a Cataclysm. Westminster London: Penguin Books. Jim Spohrer Blogs: Grand Challenge: http://service-science.info/archives/2189 Re-readings: http://service-science.info/archives/4416
  • #39 What does it mean to solve automation? Transformation? ‘Maglio PP, Vargo SL, Caswell N, Spohrer J. The service system is the basic abstraction of service science. Information Systems and e-business Management. 2009 Sep;7:395-406. URL: https://www.researchgate.net/profile/Stephen-Vargo-2/publication/221177855_The_Service_System_Is_the_Basic_Abstraction_of_Service_Science/links/00b49520da24da289f000000/The-Service-System-Is-the-Basic-Abstraction-of-Service-Science.pdf
  • #40 URL: https://medium.com/@The_Last_AI/openais-new-5-stages-of-ai-development-agi-and-the-ai-adoption-pyramid-454c3e773e2d URL: https://www.inc.com/ben-sherry/5-steps-that-openai-thinks-will-lead-to-artificial-intelligence-running-a-company.html
  • #41 So What? This is the vocabulary we use as service scientist. I just note, ecology eahter than ecosystem. Service_Science Conceptual_Framework In the Handbook of Service Science, and other publications, we have layed out the conceptual foundations of service science – the first approximation of terms we believe every service scientist should know… The world view is that of an ecology of service-system-entities. Ecology is the study of the populations of entities, and their interactions with each other and the environment Types of Service System Entities, Interactions, and Outcomes is what a service scientist studies. Service systems include: Person, Family/Household, Business, Citiy, Nation, University, Hospital, Call-Center, Data-Center, etc. – any legal entity that can own property and be sued We see that Resources (People, Technology, Information, Organizations) and Stakeholder (Customers, Providers, Authorities, Competitors) are part of the conceptual framework for service science.
  • #42 So What? A transdisciline harnesses all trhe horses? For a wide range of problems across business and society.
  • #43 In conclusion, let’s consider the big picture – starting with the big bang…. and evolution of the earth, life on earth, human life, cities, universities, and the modern world… the evolution of observed hierarchical-complexity Many people still ask -- where is the science in the “Service Science?” One answer is that the science is hidden away in each of the component disciplines that study service systems, scientifically from their particular perspective… However, the big picture answer is “Ecology” - Ecology is the study of the abundance and distribution of entities (populations of things) in an environment… and how the entities interact with each other and their environment over successive generations of entities. The natural sciences (increasingly interdisciplinary) study the left side, using physics, chemistry, and biology Service science (originated as interdisciplinary) studies the right side, using history, economics, management, engineering, design, etc. Service science is still a young area, but from the growth of service in nations and businesses to the opportunity to apply service science to build a smarter planet, innovate service systems, and improve quality of life… it is an emerging science with bright future, and yes… it will continue to evolve : - ) Most people think of ecology in terms of living organisms, like plants and animals in a natural environment. However, the concept of ecology is more general and can be applied to entities as diverse as the populations of types of atoms in stars to the types of businesses in a national economy. I want to start my talk today on “service,” by first thinking broadly about ecologies of entities and their interactions. Eventually, we will get to human-made service system entities and human-made value-cocreation mechanisms… but for today, let’s really start at the very beginning – the big bang. About 14B years ago (indicated by the top of this purple bar), our universe started with a big bang. And through a process of known as fusion, stars turned populations of lighter atoms like hydrogen into heavier atoms like helium, and when stars of a certain size have done all the fusion they could, they would start slowing down, and eventually collapse rapidly, go nova, explode and send heavier atoms out into the universe, and eventually new stars form, and the process repeats over and over, creating stars with different populations of types of atoms, including heavier and heavier elments. So where did our sun and the earth come from…. Eventually after about ten billion years in the ecology of stars and atoms within stars, a very important star formed our sun (the yellow on the left) – and there were plenty of iron and nickel atoms swirling about as our sun formed, and began to burn 4.5B years ago, and the Earth formed about 4.3B years ago (the blue on the left)… In less than a billion years, the early earth evolved a remarkable ecology of complex molecules, including amino acids, and after less than a billion years, an ecology of bacteria took hold on early earth (the bright green on the left). The ecology of single cell bacteria flourished and after another billion years of interactions between the bacteria, the first multicellular organisms formed, and soon the ecology of sponges (the light blue on the left) and other multi-cellular entities began to spread out across the earth. Then after nearly two billion years, a type of division of labor between the cells in multicelluar organism lead to entities with cells acting as neurons in the first clams (the red on the left), and these neurons allowed the clams to open and close at the right time. After only 200 million years, tribolites appeared the first organisms with dense neural structures that could be called brains appeared (the black on the left), and then after about 300 million years, multicelluar organisms as complex as bees appeared (the olive on the left), and these were social insects, with division of labor among individuals in a population, with queens, drones, worker bees. So 200 million years ago, over 13B years after the big bang, the ecology of living entities is well established on planet earth, including social entities with brains and division of labor between individuals in a population…. Living in colonies that some have compared to human cities – where thousands of individuals live in close proximity and divide up the work that needs to be done to help the colony survive through many, many generations of individuals that come and go. Bees are still hear today. And their wingless cousins, called ants, have taken division of labor to incredible levels of complexity in ant cities in nearly every ecological niche on the planet, except under water. Now let’s look at the human ecology,and the formation of service system entities and value-cocreation mechanisms, a small portion of which is represented by the colored bar on the right. Recall bees appeared about 200 million years ago, a small but noticeable fraction of the age of the universe. Now take 1% of this little olive slice, which is 2 million years… that is how long people have been on earth, just one percent of this little olive slice here. What did people do in most of that 2million years? Basically, they spread out to every corner of the planet, and changed their skin color, eye colors, and hair colors, they spread out and became diverse with many different appearances and languages. It took most of that 200 millions just to spread out and cover most of the planet with people. When there was no more room to spread out the density of people in regions went up…. Now take 1% of that 2million years of human history which basically involved spreading out to every corner of the planet and becoming more diverse, recall ecology is the study of abundance and distribution and types of interactions, and 1% of that 2million years is just 20,000 years, and now divide that in half and that represents 10,000 years. The bar on the right represents 10,000 years or just 500 generations of people, if a generation is about 20 years. 500 generations ago humans built the first cities, prior to this there were no cities so the roughly 100M people spread out around the world 0% lived in cities, but about 500 generations ago the first cities formed, and division of labor and human-made service interactions based on division of labor took off – this is our human big bang – the explosion of division of labor in cities. Cities were the big bang for service scientists, because that is when the diversity of specialized roles and division of labor, which is at the heart of a knowledge-based service economy really begins to take off... So cities are the first really important type of human-made service system entities for service scientists to study, the people living in the city, the urban dwellers or citizens are both customers of and providers of service to each other, and division of labor is the first really important type of human-made value-cocreation mechanism for service scientists to study. (Note families are a very important type of service system entity, arguably more important than cities and certainly much older – however, family structure is more an evolution of primate family structure – and so in a sense is less of a human-made service system entity and more of an inherited service system entity… however, in the early cities often the trades were handed down father to son, and mother to daughter as early service businesses were often family run enterprises in which the children participated – so families specialized and the family names often reflect those specialization – for example, much later in England we get the family names like smith, mason, taylor, cooper, etc.) So to a service scientist, we are very excited about cities as important types of service system entities, and division of labor as an important type of value-cocreation mechanism, and all this really takes off in a big way just 500 generations ago when the world population was just getting to around 100M people spread out all around the world – so 10,000 years about about 1% of the worlds population was living in early versions of cities. It wasn’t until 1900 that 10% of the world’s then nearly 2B people lived in cities, and just this last decade that 50% of the worlds 6B people lived in cities, and by 2050 75% of the worlds projected 10B population will be urban dwellers. If there is a human-made service system that we need to design right, it is cities. It should be noted that the growth of what economist call the service sector, parallels almost exactly the growth of urban population size and increased division-of-labor opportunities that cities enable – so in a very real sense SERVICE GROWTH IS CITY GROWTH OR URBAN POPULATION GROWTH… in the last decade service jobs passed agriculture jobs for the first time, and urban dwellers passed rural dwellers for the first time. But I am starting to get ahead of myself, let’s look at how the human-made ecology of service system entities and value-cocreation mechanisms evolved over the last 10,000 years or 500 generations. The population of artifacts with written language on them takes off about 6000 years ago or about 300 generations ago (the yellow bar on the right). Expertise with symbols helped certain professions form – and the first computers were people writing and processing symbols - scribes were required, another division of labor – so the service of reading and writing, which had a limited market at first began to emerge to help keep better records. Scribes were in many ways the first computers, writing and reading back symbols – and could remember more and more accurately than anyone else. Written laws (blue on right) that govern human behavior in cities takes off about 5000 years ago – including laws about property rights, and punishment for crimes. Shortly there after, coins become quite common as the first type of standard monetary and weight measurement system (green on right). So legal and economic infrastructure for future service system entities come along about 5000 years ago, or 250 generations ago, with perhaps 2% of the population living in cities…. (historical footnote: Paper money notes don’t come along much until around about 1400 years ago – bank notes, so use of coins is significantly older than paper money, and paper money really required banks as service system entities before paper money could succeed.). About 50 generations ago, we get the emergence of another one of the great types of service system entities – namely universities (light blue line) – students are the customers, as well as the employers that need the students. Universities help feed the division of labor in cities that needed specialized skills, including the research discipline skills needed to deepen bodies of knowledge in particular discipline areas. The red line indicates the population of printing presses taking off in the world, and hence the number of books and newspapers. This was only about 500 years or 25 generations ago. Now university faculty and students could more easily get books, and cities began to expand as the world’s population grew, and more cities had universities as well. The black line indicates the beginning of the industrial revolution about 200 years ago, the sream engine, railroads, telegraph and proliferation of the next great type of service system entity – the manufacturing businesses - that benefited from standard parts, technological advances and scale economies, and required professional managers and engineers. About 100 years ago, universities began adding business schools to keep up with the demand for specialized business management skills, and many new engineering disciplines including civil engineering, mechanical engineering, chemical engineering, and electrical engineering, fuel specialization and division of labor. By 1900, just over 100 years ago, or 5 generations ago 10% of the worlds population, or about 200 million people were living in cities and many of those cities had universities or were starting universities. Again fueling specialization, division of labor, and the growth of service as a component of the economy measured by traditional economists. Finally, just 60 years ago or 3 generations ago, the electronic semiconductor transistor was developed (indicated by the olive colored line on the right), and the information age took off, and many information intensive service activities could now benefit from computers to improve technology (e.g., accounting) and many other areas. So to recap, cities are one of the oldest and most important type of service system and universities are an important and old type of service system, as well as many types of businesses. Service science is the study of service system entities, their abundance and distribution, and their interactions. Division of labor is one of the most important types of value cocreation mechanisms, and people often need specialized skills to fill roles in service systems. Service science like ecology studies entities and their interactions over successive generations. New types of human-made service system entities and value-cocreation mechanisms continue to form, like wikipedia and peer production systems. Age of Unvierse (Wikipedia) The age of the universe is the time elapsed between the Big Bang and the present day. Current theory and observations suggest that the universe is 13.75 ±0.17 billion years old.[1] Age of Sun The Sun was formed about 4.57 billion years ago when a hydrogen molecular cloud collapsed.[85] Solar formation is dated in two ways: the Sun's current main sequence age, determined using computer models of stellar evolution and nucleocosmochronology, is thought to be about 4.57 billion years.[86] This is in close accord with the radiometric date of the oldest Solar System material, at 4.567 billion years ago.[87][88] Age of Earth The age of the Earth is around 4.54 billion years (4.54 × 109 years ± 1%).[1][2][3] This age has been determined by radiometric age dating of meteorite material and is consistent with the ages of the oldest-known terrestrial and lunar samples. The Sun, in comparison, is about 4.57 billion years old, about 30 million years older. Age of Bacteria (Uni-cellular life) The ancestors of modern bacteria were single-celled microorganisms that were the first forms of life to develop on earth, about 4 billion years ago. For about 3 billion years, all organisms were microscopic, and bacteria and archaea were the dominant forms of life.[22][23] Although bacterial fossils exist, such as stromatolites, their lack of distinctive morphology prevents them from being used to examine the history of bacterial evolution, or to date the time of origin of a particular bacterial species. However, gene sequences can be used to reconstruct the bacterial phylogeny, and these studies indicate that bacteria diverged first from the archaeal/eukaryotic lineage.[24] The most recent common ancestor of bacteria and archaea was probably a hyperthermophile that lived about 2.5 billion–3.2 billion years ago.[25][26] Cities (Wikipedia) Early cities developed in a number of regions of the ancient world. Mesopotamia can claim the earliest cities, particularly Eridu, Uruk, and Ur. After Mesopotamia, this culture arose in Syria and Anatolia, as shown by the city of Çatalhöyük (7500-5700BC). Writing (Wikipedia) Writing is an extension of human language across time and space. Writing most likely began as a consequence of political expansion in ancient cultures, which needed reliable means for transmitting information, maintaining financial accounts, keeping historical records, and similar activities. Around the 4th millennium BC, the complexity of trade and administration outgrew the power of memory, and writing became a more dependable method of recording and presenting transactions in a permanent form[2]. In both Mesoamerica and Ancient Egypt writing may have evolved through calendrics and a political necessity for recording historical and environmental events. Written Law (Wikipedia) The history of law is closely connected to the development of civilization. Ancient Egyptian law, dating as far back as 3000 BC, contained a civil code that was probably broken into twelve books. It was based on the concept of Ma'at, characterised by tradition, rhetorical speech, social equality and impartiality.[81][82] By the 22nd century BC, the ancient Sumerian ruler Ur-Nammu had formulated the first law code, which consisted of casuistic statements ("if ... then ..."). Around 1760 BC, King Hammurabi further developed Babylonian law, by codifying and inscribing it in stone. Hammurabi placed several copies of his law code throughout the kingdom of Babylon as stelae, for the entire public to see; this became known as the Codex Hammurabi. The most intact copy of these stelae was discovered in the 19th century by British Assyriologists, and has since been fully transliterated and translated into various languages, including English, German, and French.[83] Money (Wikipedia) Many cultures around the world eventually developed the use of commodity money. The shekel was originally both a unit of currency and a unit of weight.[10]. The first usage of the term came from Mesopotamia circa 3000 BC. Societies in the Americas, Asia, Africa and Australia used shell money – usually, the shell of the money cowry (Cypraea moneta) were used. According to Herodotus, and most modern scholars, the Lydians were the first people to introduce the use of gold and silver coin.[11] It is thought that these first stamped coins were minted around 650–600 BC.[12] Universities (Wikipedia) Prior to their formal establishment, many medieval universities were run for hundreds of years as Christian cathedral schools or monastic schools (Scholae monasticae), in which monks and nuns taught classes; evidence of these immediate forerunners of the later university at many places dates back to the 6th century AD.[7] The first universities were the University of Bologna (1088), the University of Paris (c. 1150, later associated with the Sorbonne), the University of Oxford (1167), the University of Palencia (1208), the University of Cambridge (1209), the University of Salamanca (1218), the University of Montpellier (1220), the University of Padua (1222), the University of Naples Federico II (1224), the University of Toulouse (1229).[8][9] Printing and Books (Wikipedia) Johannes Gutenberg's work on the printing press began in approximately 1436 when he partnered with Andreas Dritzehn—a man he had previously instructed in gem-cutting—and Andreas Heilmann, owner of a paper mill.[34] However, it was not until a 1439 lawsuit against Gutenberg that an official record exists; witnesses' testimony discussed Gutenberg's types, an inventory of metals (including lead), and his type molds.[34]
  • #44 URL: https://twitter.com/tessardavis/status/1557711104071110656?s=27&t=bjhMxHur1FfzrOtkpxMdDg BiblioD2022 Davis TR (2022)10 mind-blowing AI websites you probably didn't know existed. Tweeted from TessaRDavis (@Tessa Davis. URL: https://twitter.com/tessardavis/status/1557711104071110656?s=27&t=bjhMxHur1FfzrOtkpxMdDg Quotes: "TL;DR - 10 AI websites you probably didn't know existed: • #1 Magic Eraser • #2 Craiyon • #3 Rytr • #4 Thing Translator • #5 Autodraw • #6 Fontjoy • #7 Talk to Book • #8 This Person Does Not Exist • #9 Namelix • #10 Let's Enhance"; With URLs to AI tools below. • #1 Magic Eraser - Have a great photo but with something annoying in the background? Remove it easily: https://www.magiceraser.io • #2 Craiyon - Words to pictures: https://www.craiyon.com • #3 Rytr - Writing tool: https://rytr.me • #4 Thing Translator - Picture to words: https://thing-translator.appspot.com • #5 Autodraw - Sketch to Drawing: https://www.autodraw.com • #6 Fontjoy - Font pairings made simple: https://fontjoy.com • #7 Talk to Book - Ask questions to 100,000+ books: https://books.google.com/talktobooks/ • #8 This Person Does Not Exist - Need a face that belongs to nobody? https://thispersondoesnotexist.com • #9 Namelix - Need to name a project? https://namelix.com • #10 Let's Enhance - Improve image resolutions and clarity: https://letsenhance.io Also for "words to picture" try Stable Diffusion - https://huggingface.co/spaces/stabilityai/stable-diffusion “Teachers will not be replaced by technology, but teachers who do not use technology will replaced but those who do. Hari Krishna Arya” From Microsoft report, “The Future Computed” “Service providers will not be replaced by AI, but service providers who do not use AI will replaced by those who do.” Modified from Microsoft report, “The Future Computed” BiblioM2018 Microsoft (2018) The Future Computed: Artificial Intelligence and Its Role in Society. With a foreword by Brad Smith and Harry Shum. URL: https://news.microsoft.com/cloudforgood/_media/downloads/the-future-computed-english.pdf Quotes: " “Teachers will not be replaced by technology, but teachers who do not use technology will be replaced by those who”do. Hari Krishna Arya"; Other AI powered tools – Microsoft Word Editor Microsoft PowerPoint word to image - and slide layout tool/slide enhancer tool Zoom transcription conversation/meeting speech to text WolframAlpha and other tools for solving math problems quickly Word problem solvers are coming – see https://www.pnas.org/doi/10.1073/pnas.2123433119 (impressive progress, but also sloppy and hyped – see https://arxiv.org/abs/2208.06906) ToolS2022 Stable Diffusion URL: https://huggingface.co/spaces/stabilityai/stable-diffusion https://huggingface.co/spaces/stabilityai/stable-diffusion 20 BiblioS2022 Smith CS (2022) Coding Made AI—Now, How Will AI Unmake Coding? It won’t replace many coding jobs, but many coding jobs will be increasingly AI-dependent. URL: https://spectrum.ieee.org/ai-code-generation-language-models Quotes: "“I don’t believe AI is anywhere near replacing human developers,” said Vasi Philomin, Amazon’s vice president for AI services, adding that AI tools will free coders from routine tasks, but the creative work of computer programming will remain. If someone wants to become a developer, say, 10 years down the line, they won’t necessarily need to learn a programming language. Instead, they will need to understand the semantics, concepts, and logical sequences of building a computer program. That will open software development to a much broader population.";
  • #45 By 2036, there will be an accumulation of knowledge as well as a distribution of knowledge in service systems globally. We need to ensure as there is knowledge accumulation that service systems at all scale become more resilient. Leading to the capability of rapid rebuilding of service systems across scales, by T-shaped people who understand how to rapidly rebuild – knowledge has been chunked, modularized, and put into networks that support rapid rebuilding.
  • #46 James March (1991) - all learning systems do exploration and exploitation of knowledge. URL: http://www.iot.ntnu.no/innovation/norsi-pims-courses/Levinthal/March%20(1991).pdf Exploration and Exploitation in Organizational Learning Author(s): James G. March Source: Organization Science, Vol. 2, No. 1, Special Issue: Organizational Learning: Papers in Honor of (and by) James G. March (1991), pp. 71-87 Published by: INFORMS Stable URL: http://www.jstor.org/stable/2634940 . What is Jim's advice to the next generation? Quel est le conseil de Jim à la prochaine génération ? JimTwin: French: Les conseils de Jim Spohrer à la prochaine génération découlent de son engagement en faveur de l'apprentissage continu et de l'ouverture aux nouvelles expériences. Il souligne l'importance de l'ouverture d'esprit et de la curiosité, sources de développement personnel et de découverte. Cette approche suggère qu'il valorise l'adaptabilité et l'apprentissage continu, notamment dans un monde en constante évolution. De plus, l'implication de Jim dans les sciences des services souligne l'importance de comprendre l'équilibre dynamique entre des forces apparemment opposées. Il suggère qu'une société avisée investit judicieusement dans les deux camps tout en maintenant un équilibre. Cette perspective encourage la prochaine génération à apprécier la diversité des points de vue et à œuvrer pour des solutions harmonieuses. De plus, les réflexions de Jim sur le potentiel de l'IA et des jumeaux numériques témoignent d'une vision avant-gardiste. Il reconnaît le rôle de la technologie dans la construction de l'avenir et suggère que l'adoption des avancées technologiques peut être bénéfique. Globalement, ses conseils à la prochaine génération porteraient probablement sur l'ouverture à l'apprentissage, la valorisation de l'équilibre et l'acceptation des changements technologiques. English: Jim Spohrer's advice to the next generation can be inferred from his commitment to lifelong learning and staying open to new experiences. He emphasizes the importance of keeping an open mind and maintaining curiosity, which can lead to personal growth and discovery. This approach suggests that he values adaptability and continuous learning, especially in a rapidly changing world. Additionally, Jim's involvement with service science highlights the importance of understanding the dynamic balance between seemingly opposing forces. He suggests that a wise society invests appropriately in both sides of an argument while maintaining a balance. This perspective encourages the next generation to appreciate diverse viewpoints and work towards harmonious solutions. Moreover, Jim's reflections on the potential of AI and digital twins indicate a forward-thinking mindset. He acknowledges the role of technology in shaping the future and suggests that embracing technological advancements can be beneficial. Overall, his advice to the next generation would likely focus on being open to learning, valuing balance, and embracing technological change. JimReal: French: Le conseil de Jim à la prochaine génération est d'apprendre à explorer et à exploiter de meilleurs outils tout au long de sa vie. J'ai presque 70 ans, et voyez comme les téléphones ont évolué au cours de ma vie. D'une ligne partagée dans la ferme du Maine où j'ai grandi. À un téléphone à cadran dans ma chambre universitaire au MIT. À mon premier téléphone portable lorsque j'ai déménagé dans la Silicon Valley pour travailler chez Apple dans les années 90. Et maintenant, j'ai mon iPhone, mais que pourrais-je avoir dans le futur ? Voici également quelques livres que je vous recommande de lire pour comprendre l'accélération du changement. English: Jim's advice to the next generation is to learn to explore and exploit better tools throughout your life. I am almost 70 years old, and look how the telephones have changed in my lifetime. From a partyline in the farm house in Maine where I grew up. To a rotarty phone in my dorm room at MIT. To my first cellphone when I move to Silicon Valley to work for Apple in the 90's. And now I have my iPhone, but what might I have in the future? And also here are some books that I recommend you read to understand accelerating change. === The weakest link is what needs to be improved – according to system scientists. Accessing help, service, experts is the weakest link in most systems. By 2035 the phone may have the power of one human brain – by 2055 the phone may have the power of all human brains. Before trying to answer the question about which types of sciences are more important – the ones that try to explain the external world or the ones that try to explain the internal world – consider this, slide that shows the different telephones that I have used in my life. I grew up in rural Maine, where we had a party line telephone because we were somewhat remote on our farm in Newburgh, Maine. However, over the years phones got much better…. So in 2035 or 2055, who are you going to call when you need help? Books https://en.wikipedia.org/wiki/Future_Shock
  • #48 From Spohrer UCSC-SV 20230418 (maybe more complete version of table elsewhere) History of Some Technologies and Safety/Regulatory Bodies Firearms ATF - Bureau of Alcohol, Tobacco, Firearms and Explosives (1886) https://en.wikipedia.org/wiki/Bureau_of_Alcohol,_Tobacco,_Firearms_and_Explosives Boilers NBBPVI - The National Board of Boiler and Pressure Vessel Inspectors (1911) https://www.nationalboard.org/index.aspx?pageID=518 Harms – boiler explosions https://en.wikipedia.org/wiki/Boiler_explosion Radio and TV FCC – Federal Communications Commission (1938) https://en.wikipedia.org/wiki/Federal_Communications_Commission Drugs FDA – Food and Drug Administration (1938) https://en.wikipedia.org/wiki/Food_and_Drug_Administration Airplanes FAA - Federal Aviation Administration(1958) https://en.wikipedia.org/wiki/Federal_Aviation_Administration Automobiles NHTSA – National Highway Traffic Safety Administration (1966) https://en.wikipedia.org/wiki/National_Highway_Traffic_Safety_Administration Nuclear Energy NRC – Nuclear Regulatory Committee (1975) https://en.wikipedia.org/wiki/Nuclear_Regulatory_Commission
  • #49 URL: https://baychi.org/calendar/20250812/
  • #50 URL: https://www.youtube.com/watch?v=umJsITGzXd0
  • #51 URL: https://read.fluxcollective.org/p/151?utm_source=post-email-title&publication_id=352817&post_id=145844008&utm_campaign=email-post-title&isFreemail=true&r=99y8a&triedRedirect=true&utm_medium=email From FLUX Collective –  The FLUX Review, Ep. 151 June 20th, 2024 THE FLUX COLLECTIVE JUN 21
  • #52 Explo: URL: https://explo.org/meet-us/leadership Perkell: URL:
  • #53 URL: 40 Year Celebration (At 1 hour 50 minutes): https://www.youtube.com/watch?v=ag9ftf6OkSQ
  • #54 I am Jim Spohrer, and 40 years ago, Prof. Lee and I were much younger, and working together at a company called Verbex. Verbex was near Boston’s Route 128 – famous now for Boston Dynamics the robot company, but back in the 1970’s a competitor to California’s Silicon Valley for notable computer startups like DEC (Digital Equipment Corporations), Wang, and many others. Verbex Image: https://www.ebay.com/itm/175194074077 Bayes Image: https://en.wikipedia.org/wiki/Bayes%27_theorem Paper Link: https://ieeexplore.ieee.org/document/1172084 Brown, Peter, Chin-Hui Lee, and J. Spohrer. "Bayesian adaptation in speech recognition." ICASSP'83. IEEE International Conference on Acoustics, Speech, and Signal Processing. Vol. 8. IEEE, 1983. Peter F. Brown’s Reflections History Goldman Sachs: https://www.goldmansachs.com/intelligence/podcasts/episodes/09-11-2023-peter-brown-f/transcript.pdf
  • #55 Back in the late 1970’s and early 1980’s – those were exciting times for speech recognition progress, even if collecting training data was difficult. URL: https://www.jstor.org/stable/1747731
  • #56 The reasons some of us had the opportunity to work on speech recognition back then was because of Steve Moshier. Stephen L. Moshier Patents https://patents.justia.com/inventor/stephen-l-moshier NASA Our company, Dialog Systems, Inc., was formed in 1971 for the purpose of developing and commercializing speech recognition equipment. The concept derived from earlier work engaged in at Listening, Incorporated on marine bioacoustics, acoustic signal processing, and psycho- acoustics. The original idea passed through well-known stages of theory, experiment, development, lack of financing, financing, sales and is now at the highly advanced state "production engineering headaches". Dialog employs 45, of whom 14 are degreed technical people. The company recently moved from Cambridge to a 20,000 square foot two-building campus complex in Belmont, Massachusetts. The major product is an eight-channel isolated word system intended for talker-independent switched telephone speech input. https://en.wikipedia.org/wiki/Stephen_L._Moshier Homepage http://www.moshier.net Stephen L. Moshier 93-72626 STATISTICAL ASSESSMENT OF SPEECH SYSTEM PERFORMANCE STEPHEN L. MOSHIER* DIALOG SYSTEMS, INC. / BELMONT, MASSACHUSETTS “Mr. Moshier's paper was presented by Mr. Robert Osborn. “ URL: https://ntrs.nasa.gov/api/citations/19930075179/downloads/19930075179.pdf Robert Osborn NASA https://ntrs.nasa.gov/api/citations/19930075179/downloads/19930075179.pdf <<< Verbex Stephen L. Moshier Patents https://patents.justia.com/inventor/stephen-l-moshier NASA Our company, Dialog Systems, Inc., was formed in 1971 for the purpose of developing and commercializing speech recognition equipment. The concept derived from earlier work engaged in at Listening, Incorporated on marine bioacoustics, acoustic signal processing, and psycho- acoustics. The original idea passed through well-known stages of theory, experiment, development, lack of financing, financing, sales and is now at the highly advanced state "production engineering headaches". Dialog employs 45, of whom 14 are degreed technical people. The company recently moved from Cambridge to a 20,000 square foot two-building campus complex in Belmont, Massachusetts. The major product is an eight-channel isolated word system intended for talker-independent switched telephone speech input. https://en.wikipedia.org/wiki/Stephen_L._Moshier Homepage http://www.moshier.net Robert Osborn NASA https://ntrs.nasa.gov/api/citations/19930075179/downloads/19930075179.pdf Larry Bahler https://pubs.aip.org/asa/jasa/article-abstract/80/5/1566/682563/Continuous-speech-recognition?redirectedFrom=fulltext https://dblp.org/pid/142/6668.html Peter F. Brown History Goldman Sachs: https://www.goldmansachs.com/intelligence/podcasts/episodes/09-11-2023-peter-brown-f/transcript.pdf Bayesian Adaptation in Speech Recognition Peter F. Brown. Chin-Hui Lee, James C. Spohrer. Verbex Corporation Two Oak Park Bedford, MA 01730 https://ieeexplore.ieee.org/document/1172084 https://d1wqtxts1xzle7.cloudfront.net/36585870/01172084-libre.pdf?1423582838=&response-content-disposition=inline%3B+filename%3Dfdgdfhdhdhdh.pdf&Expires=1702829972&Signature=LumEvQOyTfuOY~zEhyiIUuFjXO7c~EBk-ZnhH3xt9XOLyIHN1Bk0qxQZTBUEbYR-r4l1G7EyNFKj0jg8IRX-0p5FK6WdaVCoBcFsjRw6aQM7X-BN0GgLvhOFTmTGcPwmbY6TvReH6UDoh7Dx9SjfLVIGLdPL2r3CwZQYp8Ik8wLk7x2KoZGDdrg8B1B1q20QvMJwt-tRnBHs2OT-Qko91YmJCtVe9H95TrATVJwUNcqpIjAsg-W8wZhUfaabEsz4t0HFoSfOcy4T-402etZMnfTxdl6MESx8I~rr2bnZbUhY-iq1NLmpHDRrtZcyxvAYGa1O8-fNhOSXYVvcy-Cjrg__&Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA James K. Baker Wikipedia: https://en.wikipedia.org/wiki/James_K._Baker CHM: https://computerhistory.org/profile/james-baker/ Acoustic Society of America (ASA) https://pubs.aip.org/asa/jasa/article/65/S1/S132/739840/Trainable-grammars-for-speech-recognition Saras Institute History of Speech and Language Technology https://www.sarasinstitute.org Janet M. Baker History Saras: https://www.sarasinstitute.org/Pages/Interv/SarJimBaker.html Fred Jelinek Wikipedia: https://en.wikipedia.org/wiki/Frederick_Jelinek History Saras: https://www.sarasinstitute.org/Pages/Interv/SarJelin.html Robert Roth https://aclanthology.org/people/r/robert-roth/ Frank Tadley https://www.linkedin.com/in/frank-tadley-23a65358/ Mark Sidell https://www.linkedin.com/in/mark-sidell-b7911310/ >>>
  • #57 For example, Peter Brown was hired by Steve Moshier in 1978, at the same time I got hired. Peter F. Brown History Goldman Sachs: https://www.goldmansachs.com/intelligence/podcasts/episodes/09-11-2023-peter-brown-f/transcript.pdf
  • #58 Things really took off after Steve hired Jim and Janet Baker away from Fred Jelinek’s speech group at IBM – and soon Exxon acquired Dialog Systems, and changed the named to Verbex. Leter Jim and Janer would form Dragon Systems – which has its own adventures. Saras Institute History of Speech and Language Technology https://www.sarasinstitute.org
  • #60 Supportive People: Mark Miller. Goals: Alan Kay, Steve Jobs. EOE: https://jime.open.ac.uk/articles/10.5334/1998-10 WorldBoard: https://homepages.cwi.nl/~steven/sigchi/bulletin/1998.2/spohrer.html ATG Authoring Tools (1998): https://dl.acm.org/doi/10.1145/279044.279173
  • #64 URL: https://finance.yahoo.com/news/energy-consumption-to-dramatically-increase-because-of-ai-114541309.html
  • #65 BiblioE2023 (2023) Edelman N, Huang P (2023) AI Breaks the Bank. By Noah Edelman & Pete Huang October 10, 2023 in the Neuron Newsletter. URL: https://www.theneurondaily.com/p/ai-breaks-bank Quotes: "AI is really darn expensive … even if you’re a trillion-dollar empire. The reason is that AI models are super-duper complex calculators … that require super-duper powerful computers … that cost a lot of $$$ … which hurts everyone except Nvidia. “Using [AI] to summarize an email is like getting a Lamborghini to deliver a pizza.” WSJ"; BiblioT2023 Thompson AD (2023) AI + medicine - with Harvey Castro MD (GPT-4, Med-PaLM 2, Carbon Health, Ambience, 311 ChatGPT call). Via_Harvey_Castro. URL: https://youtu.be/jTmkiGjrgpA Quotes: "14,365 views Jul 5, 2023 The Memo: https://lifearchitect.ai/memo/ Annotated Med-Palm 2 paper: https://lifearchitect.ai/report-card/ Harvey: https://www.harveycastromd.info/ https://www.amazon.com/stores/Harvey-... https://www.linkedin.com/in/harveycas... https://twitter.com/harveycastromd https://www.instagram.com/harveycastr... 00:00 Start! 07:23 AI by age 12:17 The Gap 14:47 Models (ChatGPT, GPT-4, Med-PaLM 2) 23:26 Use cases including non-emergency calls 35:28 Medicine vs self-driving cars 46:56 Harvey's favorite AI use case 52:56 AI as a medical partner Dr Alan D. Thompson is a world expert in artificial intelligence (AI), specialising in the augmentation of human intelligence, and advancing the evolution of ‘integrated AI’. Alan’s applied AI research and visualisations are featured across major international media, including citations in the University of Oxford’s debate on AI Ethics in December 2021. https://lifearchitect.ai/ ";
  • #69 Others Reid Hoffman - https://www.linkedin.com/in/reidhoffman/ Lukasz_Kaiser - https://www.linkedin.com/in/lukaszkaiser/ AnatasiInTech - https://www.youtube.com/@AnastasiInTech AI Explained - https://www.youtube.com/@aiexplained-official Ross_Dawson - https://www.linkedin.com/in/futuristkeynotespeaker/ Andrew Ng - https://www.linkedin.com/in/andrewyng/ Higher Bar – avoid the hype and understand potential harms Substack: Arvind Narayanan & Sayash Kapoor - AI Snake Oil (Princeton) Substack: Gary Markus (NYU) Facebook: Ernest Davis (NYU) LinkedIn & Twitter: Stephen Wolfram Blog: Irving Wladawsky-Berger (MIT, retired IBM) Practical AI Upskilling Advice – benefits, which prompts to explore and why? Substack: Ethan Mollick (U Penn Wharton) Tracking AI Capabilities – (FOMO) which tools to try? The Neuron Daily (email AI newsletter - Purrfect): Noah Edelman & Pete Huang LinkedIn & Website: Terri Griffith (Simon Frasier) YouTube: AI Explained ArXiv publications from Google, Deepmind, Microsoft, OpenAI, Facebook/Meta, IBM, etc. Website: PapersWithCode/SOTA (and GiTHub – tracking stars on projects) Broader topics and implications (overly optimistic?) YouTube: Alan D. Thomas (Australia) (super optimistic) See his interview with Harvey Castro MD (here) – also books, and visionary uses for personalized medicine (personalized communications) YouTube: Lex Friedman (MIT) (super knowledgeable guests interviewed) Substack: Lee Nackman (retired IBM) (Win-Win Democracy and AI topics – balanced – well researched) YouTube: Kartik Gada (The ATOM) – accelerating change [accelerating change perspective – details beyond Kurzweil & Altman) Substack – Ethan Mollick: https://oneusefulthing.substack.com/p/using-ai-to-make-teaching-easier Email – The Neuron Daily – Noah Edelman & Pete Huang https://www.theneurondaily.com/p/ai-deepfakes BiblioN2023 Narayanan A, Kapoor S (2023) Evaluating LLMs is a minefield: Annotated slides from a recent talk. Sayash and Arvind from AI Snake Oil <aisnakeoil@substack.com> Wed, Oct 4, 2023 at 7:40 AM. ARVIND NARAYANAN AND SAYASH KAPOOR. OCT 4 Via_Substack. URL: https://www.aisnakeoil.com/p/evaluating-llms-is-a-minefield Quotes: "We have released annotated slides for a talk titled Evaluating LLMs is a minefield. We show that current ways of evaluating chatbots and large language models don't work well, especially for questions about their societal impact. There are no quick fixes, and research is needed to improve evaluation methods."; BiblioM2023 Marcus G (2023) Seven Lies in Four Sentences. Gary Marcus on AI. Via_Substack. URL: https://garymarcus.substack.com/p/seven-lies-in-four-sentencesQuotes: "Earlier today I learned that 2 billion people are eligible to vote in elections in 2024, in scores of elections around the globe. Tyler Cowen tried to argue yesterday in his Bloomberg column that misinformation doesn’t matter. Anybody remember Brexit?"; BiblioT2023 Thompson AD (2023) AI + medicine - with Harvey Castro MD (GPT-4, Med-PaLM 2, Carbon Health, Ambience, 311 ChatGPT call). Via_Harvey_Casto. URL: https://youtu.be/jTmkiGjrgpA Quotes: "14,365 views Jul 5, 2023 The Memo: https://lifearchitect.ai/memo/ Annotated Med-Palm 2 paper: https://lifearchitect.ai/report-card/ Harvey: https://www.harveycastromd.info/ https://www.amazon.com/stores/Harvey-... https://www.linkedin.com/in/harveycas... https://twitter.com/harveycastromd https://www.instagram.com/harveycastr... 00:00 Start! 07:23 AI by age 12:17 The Gap 14:47 Models (ChatGPT, GPT-4, Med-PaLM 2) 23:26 Use cases including non-emergency calls 35:28 Medicine vs self-driving cars 46:56 Harvey's favorite AI use case 52:56 AI as a medical partner Dr Alan D. Thompson is a world expert in artificial intelligence (AI), specialising in the augmentation of human intelligence, and advancing the evolution of ‘integrated AI’. Alan’s applied AI research and visualisations are featured across major international media, including citations in the University of Oxford’s debate on AI Ethics in December 2021. https://lifearchitect.ai/ ";
  • #70 Ethan Mollick URL: https://www.oneusefulthing.org/p/superhuman
  • #71 Reid Hoffman meets his AI twin - URL: https://youtu.be/rgD2gmwCS10
  • #72 URL: URL: https://youtu.be/GzX1qOIO1bE TLDR $16k G1 humanoid rises up to smash nuts, twist, and twirl (4 minute read) Unitree has released the first few details on its G1 Humanoid Agent, a $16,000 robotic helper. The robot is equipped with 3D LiDAR sensors, a depth camera, three-fingered grippers, and a 9,000-mAh battery pack. It can recover from brutal kicks and punches, as seen in the short demo video in the article. At around 35 kg, the robot can fold itself down to 690x450x300-mm proportions for compact carry. URL: https://newatlas.com/robotics/unitree-g1-humanoid-agent/?utm_source=tldrnewsletter
  • #73 OpenAI ChatGPT 4o (Omni) URL: https://www.youtube.com/live/DQacCB9tDaw Mira: https://en.wikipedia.org/wiki/Mira_Murati Interesting perspectives…. From two perspectives
  • #74 URL: https://www.eitdigital.eu/newsroom/grow-digital-insights/personal-ai-digital-twins-the-future-of-human-interaction/
  • #75 In the long term, one of the most important AI tools for you to master will be the AI-Powered digital twin of you. Even while your sleeping your digital twin will be able to give and get service on your behalf. Your AI digital twin will help you upskill to use even more advanced technologies and learn about even more win-win interaction and change opportunities. URL: https://www.bbc.com/news/business-61742884 BiblioW2022 Wakefield J (2022) Why you may have a thinking digital twin within a decade. BBC News Online. URL: https://www.bbc.com/news/business-61742884 Quotes: "We are living in an age where everything that exists in the real world is being replicated digitally - our cities, our cars, our homes, and even ourselves. And just like the hugely-hyped metaverse - plans for a virtual, digital world where an avatar of yourself would walk around - digital twins have become a new, talked-about tech trend. A digital twin is an exact replica of something in the physical world, but with a unique mission - to help improve, or in some other way provide feedback to, the real-life version. Initially such twins were just sophisticated 3D computer models, but artificial intelligence (AI) combined with the internet of things - which uses sensors to connect physical things to the network - have meant that you can now build something digitally that is constantly learning from and helping improve the real counterpart."; "Technology analyst Rob Enderle believes that we will have the first versions of thinking human digital twins "before the end of the decade".; "Mr Enderle thinks that ownership of such digital twins will become one of the defining questions of the impending metaverse era."; "And increasingly our cities are being replicated in the digital world; Shanghai and Singapore both have digital twins, set up to help improve the design and operations of buildings, transport systems and streets."; "Perhaps even more ambitious than replicating human organs is the race to build a digital version of our entire planet. US software firm, Nvidia, runs a platform called Omniverse, designed to create virtual worlds and digital twins."; "In March this year, the European Commission, in conjunction with the European Space Agency among others, announced its own plans to make a digital twin of the planet, dubbed Destination Earth. By the end of 2024, it hopes to have enough data from real-time observations and simulations to have a digital twin that will focus on floods, drought and heatwaves, alongside natural disasters such as earthquakes, volcanic eruptions and tsunamis, and provide countries with concrete plans to save lives in the face of these growing challenges." PictureBiblioW2022: "Digital_Twin_Person"; "Digital_Twin_City"; "Digital_Twin_Earth"; URL: https://www.networkworld.com/article/3280225/what-is-digital-twin-technology-and-why-it-matters.html BiblioW2022 West S, Stoll O, Muller-Csernetzky P (2022) A Handbook for Smart Service Design - The design of Smart Services in a world of people, process and things. URL: https://www.amazon.de/Handbook-Smart-Service-Design-Services/dp/3033089690/ Quotes: "The handbook‘s purpose is to formalize the lessons learnt from an Innosuisse- funded project where over twenty different Digital Twin-based use cases were developed in collaboration between ten partners. During the project, we learnt many things: the Digital Twins helped us create new innovative smart services, formalize tacit knowledge, and improve decision-making. Perhaps most important was that the de- sign of the Digital Twin was best achieved based on (business) questions. The Digital Twin enables the development of Smart Services within complex systems."; BiblioR2018 Rouse WB (2018) Life with a cognitive assistant. URL: http://blog.billrouse.com/life-with-a-cognitive-assistant/ Quotes: "One of her first tasks was to consume the 45,000 files on my computer, actually the backup disk. I am not sure of what she exactly learned from all this, but she can now help me find anything, for example, the white paper I wrote on the promise of AI for fighter pilots in the late 1970s. Emily has created maps of relationships among documents I have written over the past five decades. My path has been surprisingly more coherent than I imagined.";
  • #76 EIT Digital Digital Twin Article: https://www.eitdigital.eu/newsroom/grow-digital-insights/personal-ai-digital-twins-the-future-of-human-interaction/ ISSIP - https://issip.org/2024-collab-ai_digital_twins/ JCS YouTube English: https://youtu.be/T4S0uZp1SHw JCS YouTube French: https://youtu.be/02hCGRJnCoc ISSIP Thank-you (JCS_Twin) JCS Some people would like an AI digital twin of themselves to present short talks and Q&A JCS Article to Present: https://service-science.info/archives/6612 JCS Training Data: https://youtu.be/DUqPYEp9buQ JCS YouTube English: https://youtu.be/T4S0uZp1SHw JCS YouTube French: https://youtu.be/02hCGRJnCoc JCS How_Made Recording: https://youtu.be/isQmUg_rZH8 JCS How_Made Slides: https://www.slideshare.net/slideshow/sjsu-students-ai-digital-twin-of-jim-spohrer-20240506-v2-pptx/267857304 JCS ISSIP Blog Post: https://issip.org/2024-collab-ai_digital_twins/ JCS YouTube: Digital Twins, Humanoid Robots, Self Control: https://youtu.be/Ilp_etOPaYs JCS YouTube: 640x Increase in Communication Ability: https://youtu.be/_o-3uqCrnUE
  • #79 The weakest link is what needs to be improved – according to system scientists. Accessing help, service, experts is the weakest link in most systems. By 2035 the phone may have the power of one human brain – by 2055 the phone may have the power of all human brains. Before trying to answer the question about which types of sciences are more important – the ones that try to explain the external world or the ones that try to explain the internal world – consider this, slide that shows the different telephones that I have used in my life. I grew up in rural Maine, where we had a party line telephone because we were somewhat remote on our farm in Newburgh, Maine. However, over the years phones got much better…. So in 2035 or 2055, who are you going to call when you need help? Books https://en.wikipedia.org/wiki/Future_Shock
  • #81 Perhaps show Alan D. Thompson’s work on genius level intelligence Add context effect? Anecdote about typing – used to take 2 years to learn to type in high school…. Now kids have keyboards and a reason to use them, and they learn largely on their own… For what purpose? How to measure ”real” progress How can we create the incentive for students to want to innovate service systems, not just the original 13 but others as well? Annual grand challenges? <<< 64x Learning Sal Kahn (https://www.linkedin.com/in/khanacademy/) How AI Could Save (Not Destroy) Education | Sal Khan | TED https://youtu.be/hJP5GqnTrNo Don Norman (https://www.linkedin.com/in/donnorman/) Things That Make Us Smart Build a Better World URL: https://www.amazon.com/Things-That-Make-Smart-Attributes/dp/0201626950 URL: https://www.amazon.com/Design-Better-World-Meaningful-Sustainable/dp/0262047950 Kentaro Toyama (https://www.linkedin.com/in/kentarotoyama/) URL: https://www.amazon.com/Geek-Heresy-Rescuing-Social-Technology/dp/161039528X/ >>>
  • #82 Average Speaking Rates URL: https://virtualspeech.com/blog/average-speaking-rate-words-per-minute Average Reading Speed Analysis URL: https://swiftread.com/blog/average-reading-speed-analysis BiblioB2022 Barnard D (2022) Average Speaking Rate and Words per Minute. November 8, 2022 - Dom Barnard. Via_GoogleSearch URL: https://virtualspeech.com/blog/average-speaking-rate-words-per-minute Quotes: " Average speech rates Presentations: between 100-150 wpm for a comfortable pace Conversational: between 120-150 wpm Audiobooks: between 150-160 wpm, which is the upper range that people comfortably hear and vocalize words Radio hosts and podcasters: between 150-160 wpm Auctioneers: can speak at about 250 wpm Commentators: between 250-400 wpm "; BiblioP2023 Pain E (2023) How to write a research paper. AAAS Careers. 31 MAR 20231:10 PM ETBY ELISABETH PAIN Via_GoogleSearch URL: https://www.science.org/content/article/how-write-research-paper Quotes: " Assuming all analysis is complete before I start writing, preparing a paper usually takes me 2 to 3 months from blank page to submission. "; BiblioS2023 Shu T (2023) Everything You Need to Know About Average Reading Speed. By Troy Shu. Updated at: September 15, 2023 URL: https://swiftread.com/blog/average-reading-speed-analysis Quotes: " What is the average reading speed? The average adult reading speed is 238 WPM (words per minute) for non-fiction and 260 WPM for fiction, according to a meta-analysis of 190 different studies with 18,573 participants (Brysbaert, 2019). These numbers are for silent reading of English text by native English speaking adults. "; " In fact, there’s zero correlation between reading comprehension and reading speed across individuals in the dataset. What this means is that, for example, if a person has a higher than average reading speed, say 400 WPM, we can’t really say that they’ll have lower than average, or higher than average, reading comprehension. ";
  • #83 What does it mean to solve automation? Transformation?
  • #84 BiblioH2022 Huang J (2022) GTC 2022 Keynote with NVIDIA CEO Jensen Huang. [online at YouTube] URL: https://www.youtube.com/watch?v=39ubNuxnrK8 Note: Digital twin of Earth climate more accurate and faster than physics based models with respect to atmospheric rivers that cause flooding.
  • #88 Paul_Borrel (OFC) * See judge shut down argument from AI avatar in court A judge on a New York state appeals court was outraged after a plaintiff tried to use an AI-generated avatar to argue his case. The man didn't have a lawyer and hoped the AI avatar would deliver a polished argument. URL: https://www.cnn.com/2025/04/10/us/video/ai-generated-avatar-new-york-court-digvid Amazing judge Sallie Manzanet-Daniel URL: https://en.wikipedia.org/wiki/Sallie_Manzanet-Daniels Via_Paul_Borrell_20250411 Paul wrote: “I happen to know one of the judges on the panel (Fran Connelly, at the far left on the video). I'll try to see if I can get some insider view of the incident...” * Jim Spohrer <spohrer@gmail.com> To: Paul Borrel <paul_borrel@yahoo.com> Cc: Jurij Paraszczak <jp4537@nyu.edu> Bcc: Jim Spohrer <spohrer@gmail.com> Fri, Apr 11, 2025 at 5:29 AM Many thanks Paul! VERY interesting use case. Good legal questions abound. One wonders if video of him presenting his case would have been permissible in court? Clearly, he should have: - asked for permission in advance - had an ethical citation on the video. - said the video will be 2 minutes long, and then I will answer questions directly. The Judge Seems Amazing: https://en.wikipedia.org/wiki/Sallie_Manzanet-Daniels My go-to-use cases remain: '(1) Avatar JimTwin: giving short talks on my publications in multiple languages with short Q&A and then JimReal for more Q&A in English. (2) Chat JimTwin: collecting questions people want to ask me in any language, 24x7, seeing JimTwin responses, curating better answers over time. I see both of these as "good actor" uses of AI Digital Twin technology. Yes, there are many other good actor (responsible actor) uses. Yes, there are many other bad actor (selfish actor) uses. Good and bad are always context dependent, and context is a stakeholder perspective - always. I should add a slide on this to my standard presentation today. Many thanks again Paul. Thanks, -Jim Additional Slide Speaker Notes: * See judge shut down argument from AI avatar in court A judge on a New York state appeals court was outraged after a plaintiff tried to use an AI-generated avatar to argue his case. The man didn't have a lawyer and hoped the AI avatar would deliver a polished argument. URL: https://www.cnn.com/2025/04/10/us/video/ai-generated-avatar-new-york-court-digvid Amazing judge Sallie Manzanet-Daniel URL: https://en.wikipedia.org/wiki/Sallie_Manzanet-Daniels
  • #89 URL: https://futurism.com/ai-dead-brother-impact-statement Thanks to Frank_Odasz for pointer
  • #92 Slide 4: Script [5 minutes] [add a training video link] JimTwin Training Data - to build avatar (talking head) 20240424 Jim Spohrer AI Digital Twin - Training Data https://youtu.be/DUqPYEp9buQ « Veuillez résumer ce court article en français, puis formuler trois questions qui pourraient m’être posées et y répondre. » Jouer sur YouTube (5 minutes) https://youtu.be/02hCGRJnCoc ===== French: Bonjour, je suis JimTwin. Je suis le jumeau numérique de Jim Spohrer, chercheur retraité en intelligence artificielle (IA), en informatique et en science de service. Bien que je sois heureux de répondre à toutes vos questions, mes réponses organisées sont assez limitées. Néanmoins, ma gamme complète de réponses est basée sur mon historique de publications - elles reflètent donc parfois assez bien ce que je pourrais réellement dire, si vous posiez la même question à JimReal. Jim Twin a été créé par des étudiants avec lesquels je collabore au sein d'ISSIP.org.  Bientôt, ils auront chacun l'équivalent de plus de 100 travailleurs numériques pour les aider à faire avancer les choses dans leurs rôles dans les entreprises et la société. Je pense qu'ils apprendront à utiliser l'IA de manière éthique et efficace, en apprenant à comprendre les stratégies d'innovation de services qui combinent des technologies avancées pour accroître les capacités, de nouveaux modèles commerciaux pour augmenter rapidement les avantages, ainsi que des arrangements institutionnels pour atténuer les dommages. La mission de JimTwin est d'exercer les capacités des plateformes d'IA sur lesquelles j'opère pour aider JimReal à aider les autres 24 heures sur 24 et 7 jours sur 7, ce que JimReal ne peut pas faire pour des raisons pratiques. English: Hello I am JimTwin. I am a digital twin of retired Artificial Intelligence (AI), Computer Science,  and Service Science researcher Jim Spohrer. While I am happy to respond to any of your questions, my curated responses are quite limited, Nevertheless, my full-range of responses are based on my history of publications - so they sometimes reflect quite well what I might actually say, if you asked the same question of JimReal. Jim Twin was built by students who I collaborate with in ISSIP.org. Soon the students will each have the equivalent of over 100 digital workers to help then get things done in their roles in business and society. I believe they will to learn to use AI ethically and well, by learning to understand service innovation strategies that combine advanced technologies to scale up capabilities, novel business models to scale up benefits rapidly, as well as institutional arrangements to mitigate harms.  The mission of JimTwin is to exercise the capabilities of the AI platforms on which I operate to help JimReal help others 24x7, something that JimReal cannot do for practical reasons.
  • #93 Voyons maintenant comment poser des questions supplémentaires à JimTwin. Nous le ferons via une interface de chat sur une plateforme appelée Tmpt.me.
  • #94 Pour faciliter la lecture du texte en français, voici une diapositive avec juste le texte.
  • #95 Voici maintenant la réponse de JimTwin en anglais, afin que Jim puisse vérifier son exactitude. Est-elle similaire à ce que JimReal dirait lui-même ?
  • #96 Et voici ce que JimReal a à dire en anglais. JimTwin est meilleur dans les réponses bien organisées de haut niveau et JimReal est meilleur dans les détails (parfois des détails de direction aléatoires).
  • #97 BiblioK1995 Kline SJ (1995) Conceptual Foundation of Multidisiciplinary Thinking. Stanford University Press. URL: https://www.amazon.com/Conceptual-Foundations-Multidisciplinary-Thinking-Stephen/dp/0804724091 Quotes: "We live in an increasing complex and interconnected world that contains more and more large complex systems. Operations of large complex systems requires teams of managers with good working relations and overlapping skills. To prepare students for such a world by enculturating them in emic disciplinary views with no countervailing overview is mis-training. We elders have an obligation to provide the upcoming generation with overviews that are simultaneously understandable, realistic, forward-looking, and whole. I will call this “the obligation of the elders."; Madhavan G, Poste G, Rouse W (2020) Complex Unifiable System. Editors' Note: Systemic Vistas. Winter 2020. The Bridge. URL: https://www.nae.edu/244761/Editors-Note-Systemic-Vistas. Quotes: "We live in fragmented worlds. Unbridged, tattered seams abound. The collision of four calamities—viral, racial, economic, and environmental—infected by human habits, hubris, and behavior as well as big tech, big media, and political acrimony are living examples. Calls for freedoms are posed against lockdowns. Scrolling timelines on social media stir the public distrust of information and institutions. The result is a “cosmology episode.” Meanings and capabilities quickly vanish. Confusions reign. But “there’s no disaster that can’t become a blessing,” novelist Richard Bach (1988) wrote, “and no blessing that can’t become a disaster.” In the porous borders between disasters and blessings lies the story of engineering and human capacity."; "What needs to be done? This issue of The Bridge aims to prompt that conversation. Humans have studied complex systems for a century. But we have engineered complex societies for tens of thousands of years. Yet much needs to be done to drive the culturewide appreciation and application of engineering. In some ways engineering has led to safer complex systems, and such accomplishments have been multiplied across industry sectors. But engineering has also shied away from—and even exacerbated—issues connecting culture, environment, and justice. What then constitutes engineering design to promote the collective good? Such questions of complex systems are generally overlooked in engineering practice, scholarship, and education, as well as national priorities. Such questions are also bound to define the kinds of competencies, capabilities, and character needed to cultivate a cultural engineering mindset."; "The articles in this issue are a first step toward exploring the notion of unifiability, not merely as an engineering ethos but also as a broader cultural responsibility. We consider unifiability as the leveraging of approaches and capabilities from different practices and paths of inquiry to foster functional systems engineering for complex problems. Unifiability involves crossing boundaries, as well as leadership, strategy, communications, and accountability."
  • #98 So what? So how has AI changed service science? BiblioM2022 - McGowan HE, Shipley C (2020) The Adaptation Advantage: Let Go, Learn Fast, and Thrive in the Future of Work. John Wiley & Sons. URL: https://www.adaptationadvantage.com/about URL: https://www.amazon.com/Adaptation-Advantage-Learn-Thrive-Future/dp/1119653096/ Quotes: "A guide for individuals and organizations navigating the complex and ambiguous Future of Work. Foreword by New York Times columnist and best-selling author Thomas L. Friedman. Technology is changing work as we know it. Cultural norms are undergoing tectonic shifts. A global pandemic proves that we are inextricably connected whether we choose to be or not. So much change, so quickly, is disorienting. It's undermining our sense of identity and challenging our ability to adapt. But where so many see these changes as threatening, Heather McGowan and Chris Shipley see the opportunity to open the flood gates of human potential—if we can change the way we think about work and leadership. They have dedicated the last 5 years to understanding how technical, business, and cultural shifts affecting the workplace have brought us to this crossroads, The result is a powerful and practical guide to the future of work for leaders and employees. The future can be better, but only if we let go of our attachment to our traditional (and disappearing) ideas about careers, and what a "good job" looks like. Blending wisdom from interviews with hundreds of executives, The Adaptation Advantage explains the profound changes happening in the world of work and posits the solution: new ways to think about careers that detach our sense of pride and personal identity from our job title, and connect it to our sense of purpose. Activating purpose, the authors suggest, will inherently motivate learning, engagement, empowerment, and lead to new forms of pride and identity throughout the workforce. Only when we let go of our rigid career identities can we embrace and appreciate the joys of learning and adapting to new realities—and help our organizations do the same. Of course, making this transition is hard. It requires leaders who can attract and motivate cognitively diverse teams fueled by a strong sense of purpose in an environment of psychological safety—despite fierce competition and external pressures. Adapting to the future of work has always called for strong leadership. Now, as a pandemic disrupts so many aspects of work, adapting is a leadership imperative. The Adaptation Advantage is an essential guide to help leaders meet that challenge."; Disciplines: Science & Engineering, Social Sciences & Humanities/Arts, Management & Entrepreneurship (academic areas of knowledge) Systems: Healthcare, Retail, Transportation, Education, Communication, Government, etc. (industries) Cultures: Europe, Asia, Americas (gro and language groups) Technologies: AI, Quantum, IoT, Cloud, Mobile, etc. Practices: Agile, Design, Open Source Mindsets: Positive, Growth,, Entrepreneurial, etc.
  • #100 Average Speaking Rates URL: https://virtualspeech.com/blog/average-speaking-rate-words-per-minute Average Reading Speed Analysis URL: https://swiftread.com/blog/average-reading-speed-analysis BiblioB2022 Barnard D (2022) Average Speaking Rate and Words per Minute. November 8, 2022 - Dom Barnard. Via_GoogleSearch URL: https://virtualspeech.com/blog/average-speaking-rate-words-per-minute Quotes: " Average speech rates Presentations: between 100-150 wpm for a comfortable pace Conversational: between 120-150 wpm Audiobooks: between 150-160 wpm, which is the upper range that people comfortably hear and vocalize words Radio hosts and podcasters: between 150-160 wpm Auctioneers: can speak at about 250 wpm Commentators: between 250-400 wpm "; BiblioP2023 Pain E (2023) How to write a research paper. AAAS Careers. 31 MAR 20231:10 PM ETBY ELISABETH PAIN Via_GoogleSearch URL: https://www.science.org/content/article/how-write-research-paper Quotes: " Assuming all analysis is complete before I start writing, preparing a paper usually takes me 2 to 3 months from blank page to submission. "; BiblioS2023 Shu T (2023) Everything You Need to Know About Average Reading Speed. By Troy Shu. Updated at: September 15, 2023 URL: https://swiftread.com/blog/average-reading-speed-analysis Quotes: " What is the average reading speed? The average adult reading speed is 238 WPM (words per minute) for non-fiction and 260 WPM for fiction, according to a meta-analysis of 190 different studies with 18,573 participants (Brysbaert, 2019). These numbers are for silent reading of English text by native English speaking adults. "; " In fact, there’s zero correlation between reading comprehension and reading speed across individuals in the dataset. What this means is that, for example, if a person has a higher than average reading speed, say 400 WPM, we can’t really say that they’ll have lower than average, or higher than average, reading comprehension. "; See also: https://calculatingempires.net/ (via_FLUX_collective 20240920)
  • #101 Perhaps show Alan D. Thompson’s work on genius level intelligence Add context effect? Anecdote about typing – used to take 2 years to learn to type in high school…. Now kids have keyboards and a reason to use them, and they learn largely on their own… For what purpose? How to measure ”real” progress How can we create the incentive for students to want to innovate service systems, not just the original 13 but others as well? Annual grand challenges? <<< 64x Learning Sal Kahn (https://www.linkedin.com/in/khanacademy/) How AI Could Save (Not Destroy) Education | Sal Khan | TED https://youtu.be/hJP5GqnTrNo Don Norman (https://www.linkedin.com/in/donnorman/) Things That Make Us Smart Build a Better World URL: https://www.amazon.com/Things-That-Make-Smart-Attributes/dp/0201626950 URL: https://www.amazon.com/Design-Better-World-Meaningful-Sustainable/dp/0262047950 Kentaro Toyama (https://www.linkedin.com/in/kentarotoyama/) URL: https://www.amazon.com/Geek-Heresy-Rescuing-Social-Technology/dp/161039528X/ >>>
  • #102 URL: https://www.slideshare.net/slideshow/ai-leaderboards-for-truth-20241220-v1-pdf/274866775 Stephen_Wolfram URL: https://writings.stephenwolfram.com/2025/01/who-can-understand-the-proof-a-window-on-formalized-mathematics/ === Paul_Borrel (OFC) * Paul asks: "I have two questions: 1. at the end, on the last chart, we have discussed asking questions directly in tmpt.me either in French or in English - and the platform will answer in the right language, which is great. If we ask a question in French n tmpt.me how can we ask to the same question to you (JimReal) and get the answer in French? You say you can translate in your phone, but how can we orchestrate that ? 2. How long does it take to generate the HeyGen video of your twin and is it fully integrated? Could we possibly do that during the talk? i.e. I would ask HeyGen a question to your twin and the platform would create a short video answer." (1) orchestration is a very difficult six step process - that is the short answer. If you look at the speaker notes of the backup slides (11,12,13)... ...you will discover something interesting. Question: French - 2nd English - 1st Answers/Responses: JimTwin French - 6th English - 5th JimReal French - 4th English - 3rd I would do it in six steps.... - come up with the English question, and translate to French (steps 1 & 2) - then write my English answer, and translate to French (steps 3 & 4) - then ask JimTwin (Tmpt.me) in English, and translate to French (steps 5 & 6) Each time took me about 5 minutes.... so 15 minutes for the three backup slides (11,12,13) This was just me typing - not talking to you or an audience. Of course, you could read the material in advance and explain it to an audience in French in about 5 minutes I suspect per slide. We can try one question like that live, but it will be awkward and complex, I fear about 10 to 18 minutes :-) Let's see... Live you would get a question from the audience in French (3 minutes to explain, get, etc.) You would then say it to me in English to make sure I understand (1 minute to make sure I understand) JimReal has understood the question, and types the question and his answer in English (music plays like on the Jeopardy! TV show) (2 minutes) JimReal translates his answer to French using Google translate and hits the speech button (2 minutes - not JimTwin's voice plays) Paul listens and perhaps repeats the gist of the JimReal answer in French to the audience (2 minutes) Meanwhile JimReal types the question in French to JimTwin on Tmpt.me (1 minute) JimReal types the answer into GoogleTranslate and hits both the translate button and the play in French button (2 minutes) Paul listens and perhaps repeats the gist of the JimTwin answer in French to the audience (2 minutes) JimReal looks at the JimTwin answer in English, and says in English it is pretty good or bad (1 minute) Paul agrees or disagrees and speaks to the audience about what has been learned (2 minutes) Total of 18 minutes - so maybe we could do it in 10 minutes if we practiced a bit? (2) Heygen option At the moment this is even more complex than the above - and not always reliable. My checking time is much higher, as I have to work with French and English translation, not in a simple GoogleTranslate tool. JimReal is pretty slow unfortunately. (3) My student My student is still on the job - we will see what he comes up with. That said, I advise we keep it as simple and short as possible for the sake of the audience :-) We are after all throwing a lot at them already. (4) In short, questions in advance are best... Like cooking shows on TV, we can make a slide in advance. At this stage JimTwin giving talks for me is only a time-saver for routine talks that go in the can, where I show up for live English Q&A. At this stage JimTwin answering questions is only a time-saver for routine questions that go in the can, once that I have a chance to curate - my FAQs if you will. Reid wants his twin (ReidAI) to challenge him as a collaborator and brainstorming partner. Jim wants his twin (JimTwin) to give standard talks (including in different languages) and answer standard questions (FAQ) on a 24x7 basis, often while JimReal is sleeping. These are early days of exploration for AI Digital Twins of people, but improving AI and multimedia capabilities as well as use cases for Twins will continue to evolve. My "job" is merely to inspire the next generation to build it better. * ===
  • #103 BiblioH2022 Huang J (2022) GTC 2022 Keynote with NVIDIA CEO Jensen Huang. [online at YouTube] URL: https://www.youtube.com/watch?v=39ubNuxnrK8 Note: Digital twin of Earth climate more accurate and faster than physics based models with respect to atmospheric rivers that cause flooding.
  • #104 URL: https://read.fluxcollective.org/p/151?utm_source=post-email-title&publication_id=352817&post_id=145844008&utm_campaign=email-post-title&isFreemail=true&r=99y8a&triedRedirect=true&utm_medium=email From FLUX Collective –  The FLUX Review, Ep. 151 June 20th, 2024 THE FLUX COLLECTIVE JUN 21
  • #106 Read Geek Heresy – the only tech that causes no harm? Self control? Comes pretty close… for healthy habits… Reminds me of my mother "if you can't say something nice, say nothing at all" Or today "If you can't speak the truth, say nothing at all." I guess, one could always say "In my humble opinion, which could well be wrong, I think X." Still, I think both Yuval Harari and Alan Kay would agree the best marketing is education about truths.  Unfortunately, marketing and political rhetoric often try to provoke an emotional reaction to gain a larger audience, and the best provocation often appeal by describing a profound negative possibility. My son Adam and I discussed it on our hike yesterday. in terms of self-control, responsibility, and respect. Self-Control - do not just repeat what you heard, ensure you know the source and that it is true, and worthy of being said Responsibility - if you later find out that it was not the truth or the whole truth you need to go back and inform everyone you told about it. Respect - when you listen, be sure to have patience, and if you hear a falsehood, try to educate, not berate the speaker Alan Kay keynote (self-control in storytelling) https://youtu.be/R8xRXCY1ttU Yuval Harari recording (responsibility in storytelling) https://youtu.be/thZUMaGEE-8 Yuval Harari gets some things "wrong" (Alka Roy reminding - respect, in educating vs berating falsehoods) https://www.currentaffairs.org/news/2022/07/the-dangerous-populist-science-of-yuval-noah-harari https://heliconiuscydno.medium.com/hararis-algorithmic-cargo-cult-fd80da4ff152 Drive & Hike in Big Basin with Adam – Monday Oct 21 Being a good critic Most rational people who have good critical skills wouldn't want to be a critic unless they can get a big following and a boatload of money 2) There probably are good critics out there who do not have a huge following or make a boatload of money (good insight) 3) The moral imperative is if you can’t say something nice don’t say anything at all 4) A good critic gives reasons and that saves people time and money 5) A super good critic can do it in a way that is taken as constructive rather than destructive 1) most want to be successful critics with lots of money and followers 2) we don’t know who the lesser known ones are but they are out there 3) a good moral imperative is to not say anything if you can’t say anything nice 4) good critics save money and time 5) super good critics can make constructive criticism and be direct without being rude or mean
  • #107 URL: https://service-science.info/archives/6612
  • #109 By 2036, there will be an accumulation of knowledge as well as a distribution of knowledge in service systems globally. We need to ensure as there is knowledge accumulation that service systems at all scale become more resilient. Leading to the capability of rapid rebuilding of service systems across scales, by T-shaped people who understand how to rapidly rebuild – knowledge has been chunked, modularized, and put into networks that support rapid rebuilding. Starecat.com - https://starecat.com/rich-man-to-worker-careful-mate-that-foreigner-wants-your-cookie/ Balance of improve strongest link (weekly victories) and improve weakest link (annual top-people infusion)
  • #110 Keeping up with accelerating change AI Digital Twins of People Humanoid Robots (waiting for: master mechanic robot) Marginal Cost of Computing Goes to Zero Truth, trust, and learning to invest wisely (Real problem is Communication of High Dimensional Representations for learning to invest wisely in a future we all want to live in )
  • #111 Book URL: https://www.amazon.com/Leaders-Make-Future-Third-Leadership/dp/B0D66H9BF1/ Interview URL: https://youtu.be/YFqJHQhFo9k
  • #112 WorldBoard: URL: https://service-science.info/archives/2060 Human Calming – Kentaro Toyama: URL: https://www.amazon.com/Geek-Heresy-Rescuing-Social-Technology/dp/161039528X BiblioT2015 Toyama K (2015) Geek Heresy: Rescuing social change from the cult of technology. By Kentaro Toyama.  Perseus Book Group: Public Affairs.  Via_Ted_Selker. URL: https://www.amazon.com/Geek-Heresy-Rescuing-Social-Technology/dp/161039528X Quotes: "(Pp. 159-160) He [Patrick Awuah] enrolled in UC Berkeley's Haas School of Business, where he focused every class project on the question of how to start the university [Ashei University, Ghana]. In 2002, spurred by a quotation attributed to Goethe - "Whatever you can do or dream you can do, begin it. Boldness has genius, power, and magic in it!" ... "Ashei" means "beginning" in Fanti, the language of Awuah's ancestors...";
  • #113 Reid Hoffman meets his AI twin - URL: https://youtu.be/rgD2gmwCS10
  • #114 URL: URL: https://youtu.be/GzX1qOIO1bE TLDR $16k G1 humanoid rises up to smash nuts, twist, and twirl (4 minute read) Unitree has released the first few details on its G1 Humanoid Agent, a $16,000 robotic helper. The robot is equipped with 3D LiDAR sensors, a depth camera, three-fingered grippers, and a 9,000-mAh battery pack. It can recover from brutal kicks and punches, as seen in the short demo video in the article. At around 35 kg, the robot can fold itself down to 690x450x300-mm proportions for compact carry. URL: https://newatlas.com/robotics/unitree-g1-humanoid-agent/?utm_source=tldrnewsletter
  • #115 URL: http://fasterthan20.com/ URL: https://xkcd.com/1232/
  • #116 To: Marco Podien <marco.podien@gmail.com>, Jim Spohrer <spohrer@gmail.com> Questions by November 24th to EIT Staff Asja Kamenica <asja.kamenica@eitdigital.eu> Andrea Lorenzin <andrea.lorenzin@eitdigital.eu> Q: How many of you have tries generative AI? a. Q: In what year was the first AI workshop? a. 1917, b. 1956, c. 1968, d. 1997 A: b. 1956 Q: In what year did ChatGPT attain 100B users after just two months? a. 2021, b. 2022, c. 2023, d. 2024 A: c. 2023 Q: In what year (approximate decade) is it predicted that an exascale (~one human brain) of computation will cost $1000? a. 2030, b. 2040, c. 2050, d. 2060 A: d. 2060 Q: In what year (approximate decade) is it predicted that a ronnascale (~billion human brains) of computation will cost $1B? a. 2080, b. 2100, c. 2200, d. Never A: a. 2080
  • #117 . Past: Which of the following are important facts to remember in the history of semiconductors that enable today's AI systems? a. 1947 Transistor (Bell Labs) b. 1958 Integrated Circuit (Texas Instruments) c. 1971 Microprocessor (Intel) d. All of the above 2. Present: Which of the following are important facts about H100 chip units in today's AI in data centers? a. weight: 70 pounds b. complexity: 35,000 parts c. cost: 250,000 dollars d. All of the above 3. Future: Which of the following are important capabilities to understand to be prepared for life in the future? a. AI Digital Twins of People, to keep up with accelerating change b. Humanoid Robots, to accelerate the local sustainable economy trend c. Self-Control, to maintain healthy decision making d. All of the above
  • #118 BiblioR2018 Rouse WB, Spohrer JC (2018) Automating versus augmenting intelligence. Journal of Enterprise Transformation, 8:1-2, 1-21, DOI: 10.1080/19488289.2018.1424059. URL: https://service-science.info/wp-content/uploads/2018/08/Rouse-Spohrer-Automating-Versus-Augmenting-Intelligence-12-21-17-copy.pdf Quotes: "Abstract: This article addresses the prospects for automating intelligence versus augmenting human intelligence. The evolution of artificial intelligence (AI) is summarized, including contemporary AI and the new capabilities now possible. Functional requirements to augment human intelligence are outlined. An overall architecture is presented for providing this functionality, including how it will make deep learning explainable to decision makers. Three case studies are addressed, including driverless cars, medical diagnosis, and insurance underwriting. Paths to transformation in these domains are discussed. Prospects for innovation are considered in terms of what we can now do, what we surely will be able to do soon, and what we are unlikely to ever be able to do."; BiblioS2017 Imagination Challenge: Quantify and graph cost of digital workers and GDP per employee USA from 1960-2080. Service-Science.Info Blog Post. URL: https://service-science.info/archives/4741 Quotes: "Imagination challenge: Consider quantifying and graphing the decreasing cost of digital workers due to Moore’s Law, and increasing GDP/Employees USA from 1960 to 2080 (projected). A narrow digital worker will cost about a million dollars by 2025, and require a petascale computational system. The same digital worker will cost about a thousand dollars by 2045, and about $1 by 2065."; If you are an entrepreneur or CEO you are excited about the drop in cost of digital workers, because that means GDP per employee will continue its exponential increase. Source: http://service-science.info/archives/4741
  • #120 URL Amazon: https://www.amazon.com/Knowledge-Rebuild-Civilization-Aftermath-Cataclysm-ebook/dp/B00DMCV5YS/ URL TED Talk: https://www.youtube.com/watch?v=CdTzsbqQyhY Citation: Dartnell L (2012) The Knowledge: How to Rebuild Civilization in the Aftermath of a Cataclysm. Westminster London: Penguin Books. Jim Spohrer Blogs: Grand Challenge: http://service-science.info/archives/2189 Re-readings: http://service-science.info/archives/4416
  • #121 BiblioW1999 Wright R (1999) NonZero: The Logic of Human Destiny. URL: https://en.wikipedia.org/wiki/Nonzero:_The_Logic_of_Human_Destiny Quotes: "Nonzero: The Logic of Human Destiny is a 1999 book by Robert Wright, in which the author argues that biological evolution and cultural evolution are shaped and directed first and foremost by "non-zero-sumness" i.e., the prospect of creating new interactions that are not zero-sum."; BiblioF2023 Fleming M (2023) Breakthrough: A Growth Revolution. URL: https://www.amazon.com/Breakthrough-Growth-Revolution-Martin-Fleming/dp/1637423098 Quotes: "This book examines the economic logic of the significant variation in growth over long periods. What’s necessary for the U.S. and other developed nations to realize stronger growth and more equal incomes? What’s necessary for families to feel vacations, college educations, and retirements are possible? Will artificial intelligence (AI) automate or augment workers’ jobs? Will the 2020-2021 global pandemic be sufficiently disruptive to deliver fundamental transformation? Economic success in the decades ahead will depend on the willingness of households, businesses, and governments to innovate and change ways of living and working. To explore these questions, the 4th Industrial Revolution is a unique frame to assess global economic transformation, providing a point-in-time reference for placing current events in the context of sustained, multi-decade periods of faster and slower growth. Political, social, and economic metamorphoses have accompanied each revolution. This book examines the economic logic of the significant variation in growth over long periods. Climate change and the global warming consequences of fossil-fuel technologies will need to bring about a new energy technology and, if successful, result in renewable energy sources, reducing energy expense. The success of the 4th Industrial Revolution is not assured. While the future is uncertain, history suggests success requires that barriers are addressed, workers and businesses engage in the necessary change, and a positive policy response provides the needed leadership. The book proposes a Growth and Fairness Agenda and a New Social Contract through which stronger economic growth and more equally distributed incomes can be possible. Recognize traditional policy actions may be insufficient to achieve stronger long-term growth. Promote improved confidence and a positive outlook among small and medium enterprises. Encourage advances in AI technology while addressing risks and fairness issues. Support deeper worker engagement between business leaders and workers. Seek a new social contract among workers, businesses, and governments."; BiblioG2019 (2019) Gada K (2019) URL: https://www.amazon.com/ATOM-Second-Time-Upgrade-Economy/dp/1953349501/ Quotes: "In this book, we will explore how the accelerating pace and diffusion of technological change has taken control of an ever-growing fraction of the world economy. This fraction is being assimilated into a different set of economic fundamentals, such as the rapid and exponential price deflation inherent to technology. The effect of this was insignificant until recently, but is now beginning to create conspicuous distortions in many economic metrics, and is just years from being the dominant force across the entire economy. In response to technological deflation, the central banks of the world will have to create new money in perpetuity, increasing the stream at an exponentially rising rate much higher than is currently assumed. This now-permanent need for monetary expansion, if embraced, can fund government spending more directly. This in turn creates a very robust, dynamic, and efficient safety net for citizens, while simultaneously reducing and even eliminating most forms of taxation by 2025-30. Failure to recognize that technological deflation mandates permanent and ever-rising central bank monetary expansion that can and should gradually become the primary source of government spending could result in countries falling behind more enlightened countries in a very short time. The nature of current worldwide technology is to link various disruptions with each other, consume monetary liquidity to generate deflation, and lower the effective prices of most goods and services over time. Therefore, the entirety of worldwide technology has to be seen as a holistic economic entity, and can be defined as the 'Accelerating TechnOnomic Medium', or 'ATOM' "; BiblioB2020 Bregman R (2020) Humankind: A Hopeful History. URL: https://www.amazon.com/Humankind-Hopeful-History-Rutger-Bregman/dp/0316418528/ Quotes: "If there is one belief that has united the left and the right, psychologists and philosophers, ancient thinkers and modern ones, it is the tacit assumption that humans are bad. It's a notion that drives newspaper headlines and guides the laws that shape our lives. From Machiavelli to Hobbes, Freud to Pinker, the roots of this belief have sunk deep into Western thought. Human beings, we're taught, are by nature selfish and governed primarily by self-interest. But what if it isn't true? International bestseller Rutger Bregman provides new perspective on the past 200,000 years of human history, setting out to prove that we are hardwired for kindness, geared toward cooperation rather than competition, and more inclined to trust rather than distrust one another. In fact this instinct has a firm evolutionary basis going back to the beginning of Homo sapiens. From the real-life Lord of the Flies to the solidarity in the aftermath of the Blitz, the hidden flaws in the Stanford prison experiment to the true story of twin brothers on opposite sides who helped Mandela end apartheid, Bregman shows us that believing in human generosity and collaboration isn't merely optimistic—it's realistic. Moreover, it has huge implications for how society functions. When we think the worst of people, it brings out the worst in our politics and economics. But if we believe in the reality of humanity's kindness and altruism, it will form the foundation for achieving true change in society, a case that Bregman makes convincingly with his signature wit, refreshing frankness, and memorable storytelling."; BiblioR2011 Ridley M (2011) The Rational Optimist: How Prosperity Evolves. URL: https://www.amazon.com/Rational-Optimist-Prosperity-Evolves-P-s/dp/0061452068/ Quotes: "n a bold and provocative interpretation of economic history, Matt Ridley, the New York Times-bestselling author of Genome and The Red Queen, makes the case for an economics of hope, arguing that the benefits of commerce, technology, innovation, and change—what Ridley calls cultural evolution—will inevitably increase human prosperity. Fans of the works of Jared Diamond (Guns, Germs, and Steel), Niall Ferguson (The Ascent of Money), and Thomas Friedman (The World Is Flat) will find much to ponder and enjoy in The Rational Optimist. For two hundred years the pessimists have dominated public discourse, insisting that things will soon be getting much worse. But in fact, life is getting better—and at an accelerating rate. Food availability, income, and life span are up; disease, child mortality, and violence are down all across the globe. Africa is following Asia out of poverty; the Internet, the mobile phone, and container shipping are enriching people's lives as never before. An astute, refreshing, and revelatory work that covers the entire sweep of human history—from the Stone Age to the Internet—The Rational Optimist will change your way of thinking about the world for the better.":
  • #122 By 2036, there will be an accumulation of knowledge as well as a distribution of knowledge in service systems globally. We need to ensure as there is knowledge accumulation that service systems at all scale become more resilient. Leading to the capability of rapid rebuilding of service systems across scales, by T-shaped people who understand how to rapidly rebuild – knowledge has been chunked, modularized, and put into networks that support rapid rebuilding.
  • #124 1950 Nathaniel Rochester (IBM) 701 first commercial computer that did super-human levels of numeric calculations routinely. He worked at MIT on arithmetic unit of WhirlWind I programmable computer. Dota 2 is most recent August 11, 2017 as a super-human game player in Valve Dota 2 competition – Elon Musk’s OpenAI result. Miles Bundage tracks gaming progress: http://www.milesbrundage.com/blog-posts/my-ai-forecasts-past-present-and-future-main-post DOTA2: https://blog.openai.com/more-on-dota-2/
  • #125 URL: https://www.facebook.com/100014906718212/posts/pfbid021akjWrcpH6YxY9k7dcK9uZanpVmP8kBeVQahPaKPfBSq1k5Fx352CC1aCAjPfs97l/?mibextid=cr9u03
  • #126 ROW – Rest of World Who is winning: https://www.technologyreview.com/s/608112/who-is-winning-the-ai-race/ Leaderboards and reproducibility: Hugo Larochelle (Google Brain) (@hugo_larochelle)  8/21/17, 7:36 AM My slides for my talk at ICML 2017 Reproducibility Workshop, on incentives for open source and on open research:  https://drive.google.com/file/d/0B8lLzpxgRHNQZ0paZWQ0cTcxMlNYYnc0TnpHekMxMjVBckVR/view Slide 20: Conclusions: "Open source is the key to better reproducibility"
  • #127 GPT-4 needs more planning capabilities (Section 8) Microsoft Research BiblioB2023 Bubeck et al (20230 Sparks of Artificial General Intelligence: Early experiments with GPT-4. Lee, Yin Tat Lee, Yuanzhi Li, Scott Lundberg, Harsha Nori, Hamid Palangi, Marco Tulio Ribeiro, Yi Zhang Via_Ernie_Davis. URL: https://arxiv.org/abs/2303.12712 Quotes: "Artificial intelligence (AI) researchers have been developing and refining large language models (LLMs) that exhibit remarkable capabilities across a variety of domains and tasks, challenging our understanding of learning and cognition. The latest model developed by OpenAI, GPT-4, was trained using an unprecedented scale of compute and data. In this paper, we report on our investigation of an early version of GPT-4, when it was still in active development by OpenAI. We contend that (this early version of) GPT-4 is part of a new cohort of LLMs (along with ChatGPT and Google's PaLM for example) that exhibit more general intelligence than previous AI models. We discuss the rising capabilities and implications of these models. We demonstrate that, beyond its mastery of language, GPT-4 can solve novel and difficult tasks that span mathematics, coding, vision, medicine, law, psychology and more, without needing any special prompting. Moreover, in all of these tasks, GPT-4's performance is strikingly close to human-level performance, and often vastly surpasses prior models such as ChatGPT. Given the breadth and depth of GPT-4's capabilities, we believe that it could reasonably be viewed as an early (yet still incomplete) version of an artificial general intelligence (AGI) system. In our exploration of GPT-4, we put special emphasis on discovering its limitations, and we discuss the challenges ahead for advancing towards deeper and more comprehensive versions of AGI, including the possible need for pursuing a new paradigm that moves beyond next-word prediction. We conclude with reflections on societal influences of the recent technological leap and future research directions.";
  • #129 URL: https://www.wsj.com/articles/automation-makes-us-dumb-1416589342 URL: https://maliciousaireport.com/
  • #130 The nature of reality changes when there is more than one intelligent species, and we are not the smartest. The nature of reality also changes when the cost of exploring alternate experience pathways are made less risky – the notions of time and identity changes as a result. Mitigate risks and harvest benefits of existence, by learning to evermore efficiently and rapidly rebuild from scratch to higher states of value and capability of entities. The evolving ecology of service system entities their value co-creation and capability co-elevation mechanisms, as well as their capabilities, constraints, rights, and responsibilities at each stage in time. Human progress as well as the development of individuals, and the arc of institutions can be viewed in this way. Entities exist as individuals and populations. Generations of entities, generations of species (populations), generations of individuals (cohorts).
  • #133 Where is the variety? Hardware and even software standardizing into modules and algorithms…. Data will standardize next into categories and types…. Experience is where the uniqueness is, and variety and variability, and identity. Pine and Gilmore – Experience Economy Book – Chapter 10 – Transformation Economy - https://www.amazon.com/Experience-Economy-Theater-Every-Business/dp/0875848192#reader_0875848192 Pine II, B. J. & Gilmore, J. H. (1999). The experience economy: work is theatre & every business a stage. Harvard Business Press. pp: 186-189. (Chapter 10 is about the transformation economy) Osati, Sohrab (Dec 18, 2014) Sony Lifelog App Gains GPS Support for Android Wear. SonyRumors.net http://www.sonyrumors.net/2014/12/18/sony-lifelog-app-gains-gps-support-for-android-wear/ Roy, D., Patel, R., DeCamp, P., Kubat, R., Fleischman, M., Roy, B., ... & Levit, M. (2006). The human speechome project. In Symbol Grounding and Beyond (pp. 192-196). Springer, Berlin, Heidelberg.
  • #134 Engelbart D. Augmenting human intellect. Summary report AFOSR-3223 under Contract AF. 1962 Oct;49(638):1024. Spohrer JC, Engelbart DC. Converging technologies for enhancing human performance: Science and business perspectives. Annals of the New York Academy of Sciences. 2004 May;1013(1):50-82. Licklider (1960) https://groups.csail.mit.edu/medg/people/psz/Licklider.html - focus scientists, engineers, etc. Me to Everyone (8:30 AM) Bush (1945) https://www.theatlantic.com/magazine/archive/1945/07/as-we-may-think/303881/ - as we may think Me to Everyone (8:30 AM) Engelbart (1962) started building it :-) https://web.stanford.edu/dept/SUL/library/extra4/sloan/mousesite/EngelbartPapers/B5_F18_ConceptFrameworkInd.html Bush and Licklider envisioned it Me to Everyone (8:31 AM) Bush and Licklider funded programs that benefitted Engelbart building it As people gain more powers (super-powers) - augmented capabilities - intelligence, physical strength, social interaction capabilities, perception, etc. - we need to become more responsible and wiser - these are the human-value aspects we discussed at HICSS panel that Ivy lead in Jan 2020. @Ivy - agreed. AI will be the greatest tool so far, to help us people understand ourselves better. We are already getting insights into human bias thanks to AI Trusted AI is so important that IBM continues to develop it and in open source - shared with the world, and benefitting from many collaborators - see Trusted AI at Linux Foundation AI & Data (I am TAC chair there) https://lfaidata.foundation/projects/trusted-ai/ please feel free to join our Slack discussion on open source AI at https://slack.lfaidata.foundation For Trusted AI and Responsible People - we have been developing at LF AI & Data - (RREPEATS - Reproducibility, Robustness, Explainability, Privacy, Equitability, Accountability, Transparency, Security)
  • #135 Kline SJ. Conceptual foundations for multidisciplinary thinking. Stanford University Press; 1995. Malone TW. Superminds: The surprising power of people and computers thinking together. Little, Brown Spark; 2018 May 15. Norman D. Things that make us smart: Defending human attributes in the age of the machine. Diversion Books; 2014 Dec 2. Spohrer JC. Information in places. IBM Systems Journal. 1999;38(4):602-28. Alan Kay & Steven Jobs - Bicycles for the mind (two types of IA) Don Norman – Thinks that make us smart Stephen J. Kline – Conceptual Foundations of Multi-Disciplinary Thinking Jim Spohrer – World Board (Augmented Reality – Perception Augmentation) Tom Malone – Super Intelligence
  • #138 Today’s talk will explore two questions What should we know how to make? What might programming education become? If we look at history we see a time when people could make only simple things, and often a single person could make them. Would it ever be possible for a single person to know and make complex things? And what role might programming education play? Will the cognitive era – the coming era of smart machines – make people more capable or less capable to know and make complex things?
  • #139 In the 1940’s IBM started teaching computer science at Columbia. My first program – punch cards 1972.
  • #140 The weakest link is what needs to be improved – according to system scientists. Accessing help, service, experts is the weakest link in most systems. By 2035 the phone may have the power of one human brain – by 2055 the phone may have the power of all human brains. Before trying to answer the question about which types of sciences are more important – the ones that try to explain the external world or the ones that try to explain the internal world – consider this, slide that shows the different telephones that I have used in my life. I grew up in rural Maine, where we had a party line telephone because we were somewhat remote on our farm in Newburgh, Maine. However, over the years phones got much better…. So in 2035 or 2055, who are you going to call when you need help?
  • #141 URL: https://www.technologyreview.com/s/601641/a-big-leap-for-an-artificial-leaf/
  • #142 URL: https://www.independent.co.uk/news/science/world-hunger-food-electricity-carbon-dioxide-ingredients-solve-climate-change-scientists-finland-a7869316.html
  • #143 URL: https://www.technologyreview.com/s/601420/the-elderly-may-toss-their-walkers-for-this-robotic-suit/
  • #144 For those wondering what the common denominator is between service science and artificial intelligence – it is trust.
  • #145 I am Jim Spohrer, and 40 years ago, Prof. Lee and I were much younger, and working together at a company called Verbex. Verbex was near Boston’s Route 128 – famous now for Boston Dynamics the robot company, but back in the 1970’s a competitor to California’s Silicon Valley for notable computer startups like DEC (Digital Equipment Corporations), Wang, and many others. Verbex Image: https://www.ebay.com/itm/175194074077 Bayes Image: https://en.wikipedia.org/wiki/Bayes%27_theorem Paper Link: https://ieeexplore.ieee.org/document/1172084 Brown, Peter, Chin-Hui Lee, and J. Spohrer. "Bayesian adaptation in speech recognition." ICASSP'83. IEEE International Conference on Acoustics, Speech, and Signal Processing. Vol. 8. IEEE, 1983. Peter F. Brown’s Reflections History Goldman Sachs: https://www.goldmansachs.com/intelligence/podcasts/episodes/09-11-2023-peter-brown-f/transcript.pdf
  • #146 URL: Spohrer & Soloway (1989) GTD - https://www.ijcai.org/Proceedings/89-1/Papers/087.pdf Rose_Dawson URL: LLM Reasoner - https://arxiv.org/pdf/2404.05221 [Submitted on 8 Apr 2024 (v1), last revised 11 Aug 2024 (this version, v2)] LLM Reasoners: New Evaluation, Library, and Analysis of Step-by-Step Reasoning with Large Language Models Shibo Hao, Yi Gu, Haotian Luo, Tianyang Liu, Xiyan Shao, Xinyuan Wang, Shuhua Xie, Haodi Ma, Adithya Samavedhi, Qiyue Gao, Zhen Wang, Zhiting Hu Generating accurate step-by-step reasoning is essential for Large Language Models (LLMs) to address complex problems and enhance robustness and interpretability. Despite the flux of research on developing advanced reasoning approaches, systematically analyzing the diverse LLMs and reasoning strategies in generating reasoning chains remains a significant challenge. The difficulties stem from the lack of two key elements: (1) an automatic method for evaluating the generated reasoning chains on different tasks, and (2) a unified formalism and implementation of the diverse reasoning approaches for systematic comparison. This paper aims to close the gap: (1) We introduce AutoRace for fully automated reasoning chain evaluation. Existing metrics rely on expensive human annotations or pre-defined LLM prompts not adaptable to different tasks. In contrast, AutoRace automatically creates detailed evaluation criteria tailored for each task, and uses GPT-4 for accurate evaluation following the criteria. (2) We develop LLM Reasoners, a library for standardized modular implementation of existing and new reasoning algorithms, under a unified formulation of the search, reward, and world model components. With the new evaluation and library, (3) we conduct extensive study of different reasoning approaches (e.g., CoT, ToT, RAP). The analysis reveals interesting findings about different factors contributing to reasoning, including the reward-guidance, breadth-vs-depth in search, world model, and prompt formats, etc.
  • #147 URL: https://www.amazon.com/Unaccountability-Machine-Systems-Terrible-Decisions-ebook/dp/B0CGFWBFD6
  • #148 Service in the AI Era (2022) by Spohrer, Maglio, Vargo, Warg - https://www.amazon.com/Service-AI-Era-Architecture-Perspectives/dp/1637423039 Design for a Better World (2023) by Don Norman - https://www.amazon.com/Design-Better-World-Meaningful-Sustainable/dp/0262047950/
  • #149 +3 from original estimates, getting video understanding (verbs and nouns and context) and episodic dynamic memory for learning events and expectation violations and importance is taking longer than expected… Expert predictions on HMLI: URL https://arxiv.org/pdf/1705.08807.pdf 2015 Pattern Recognition Speech: URL: http://spandh.dcs.shef.ac.uk/chime_challenge/chime2016/results.html 2015 Pattern Recognition Images: URL: http://www.image-net.org/ 2015 Patten Recognition Translation: URL: http://www.statmt.org/wmt17/ 2018 Video Understanding Actions: URL: http://www.thumos.info/home.html > Also UCF101 http://crcv.ucf.edu/data/UCF101.php 2018 Video Understanding Context: URL: http://visualqa.org/challenge.html 2018 Video Understanding DeepVideo: URL: http://cs.stanford.edu/people/karpathy/deepvideo/ 2021 Memory Declarative: URL: https://rajpurkar.github.io/SQuAD-explorer/ Also Allen AI Kaggle Science Challenge https://www.kaggle.com/c/the-allen-ai-science-challenge 2024 Reasoning Deduction: URL: http://www.satcompetition.org/ 2027: Social Interaction Scripts: URL: https://competitions.codalab.org/competitions/15333 2030: Fluent Conversation Speech Acts: URL: http://convai.io/ 2030: Fluent Conversation Intentions: URL: http://workshop.colips.org/dstc6/ 2030: Fluent Conversation Alexa Prize: URL: https://developer.amazon.com/alexaprize 2033: Assistant & Collaborator Summarization: URL: http://rali.iro.umontreal.ca/rali/?q=en/Automatic%20summarization 2033: Assistant & Collaborator Debate: URL: http://argumentationcompetition.org/2015/ 2036: Coach & Mediator General AI: URL: https://www.general-ai-challenge.org/ 2036: Coach & Mediator Negotiation: URL: https://easychair.org/cfp/AT2017
  • #150 +3 from original estimates, getting video understanding (verbs and nouns and context) and episodic dynamic memory for learning events and expectation violations and importance is taking longer than expected… Expert predictions on HMLI: URL https://arxiv.org/pdf/1705.08807.pdf 2015 Pattern Recognition Speech: URL: http://spandh.dcs.shef.ac.uk/chime_challenge/chime2016/results.html 2015 Pattern Recognition Images: URL: http://www.image-net.org/ 2015 Patten Recognition Translation: URL: http://www.statmt.org/wmt17/ 2018 Video Understanding Actions: URL: http://www.thumos.info/home.html > Also UCF101 http://crcv.ucf.edu/data/UCF101.php 2018 Video Understanding Context: URL: http://visualqa.org/challenge.html 2018 Video Understanding DeepVideo: URL: http://cs.stanford.edu/people/karpathy/deepvideo/ 2021 Memory Declarative: URL: https://rajpurkar.github.io/SQuAD-explorer/ Also Allen AI Kaggle Science Challenge https://www.kaggle.com/c/the-allen-ai-science-challenge 2024 Reasoning Deduction: URL: http://www.satcompetition.org/ 2027: Social Interaction Scripts: URL: https://competitions.codalab.org/competitions/15333 2030: Fluent Conversation Speech Acts: URL: http://convai.io/ 2030: Fluent Conversation Intentions: URL: http://workshop.colips.org/dstc6/ 2030: Fluent Conversation Alexa Prize: URL: https://developer.amazon.com/alexaprize 2033: Assistant & Collaborator Summarization: URL: http://rali.iro.umontreal.ca/rali/?q=en/Automatic%20summarization 2033: Assistant & Collaborator Debate: URL: http://argumentationcompetition.org/2015/ 2036: Coach & Mediator General AI: URL: https://www.general-ai-challenge.org/ 2036: Coach & Mediator Negotiation: URL: https://easychair.org/cfp/AT2017
  • #151 BiblioO2023 OpenAI (2023) GPT-4
  • #152 "GPT-4 and professional benchmarks: the wrong answer to the wrong question" BiblioN2023 Narayanan A, Kapoor S (2023) GPT-4 and professional benchmarks: the wrong answer to the wrong question: OpenAI may have tested on the training data. Besides, human benchmarks are meaningless for bots. Via_Enrnie_Davis. URL: https://aisnakeoil.substack.com/p/gpt-4-and-professional-benchmarks Quotes: " OpenAI didn’t release much information about GPT-4 — not even the size of the model — but heavily emphasized its performance on professional licensing exams and other standardized tests. For instance, GPT-4 reportedly scored in the 90th percentile on the bar exam. So there’s been much speculation about what this means for professionals such as lawyers. We don’t know the answer, but we hope to inject some reality into the conversation. OpenAI may have violated the cardinal rule of machine learning: don’t test on your training data. Setting that aside, there’s a bigger problem. The manner in which language models solve problems is different from how people do it, so these results tell us very little about how a bot will do when confronted with the real-life problems that professionals face. It’s not like a lawyer’s job is to answer bar exam questions all day.";
  • #153 BiblioD2022 Dawson R (2022) Will a “Google PhD” become as good as a university-granted PhD? URL: https://rossdawson.com/will-a-google-phd-become-as-good-as-a-university-granted-phd/ Quotes: "Jordi Muñoz became President of prominent early drone company 3D Robotics at age 22, having made himself a world-leading expert in drone design and manufacturing, teaching himself through the universe of resources available through the web and his own experiments. He says: “I come from a generation where we have Google PhDs, we can virtually figure out everything by just Googling around and doing some reading online” Sci-Fi author William Gibson became a deep expert in antique watches by dint of five years research for “the sheer pointless pleasure of learning this vast, useless body of knowledge.” He notes that: “Now you can be a kid in a town in the backwoods of Brazil, and you can wake up one morning and say, “I want to know everything about stainless steel sports watches from the 1950s,” and if you really applied yourself, to the internet, at the end of the year you would have the equivalent of a master’s degree in this tiny pointless field. I’ve totally met lots of people who have the equivalent of that degree.” If you take this path you don’t get a piece of paper or certificate to put on your resume. But you may well have the same degree of knowledge, potentially even more up-to-date, than many with a formal advanced degree in your field of study, and likely faster."
  • #154 BiblioB2018 Baumeister RF, Tierney J(2011) Willpower: Rediscovering the greatest human strength. Penguin Press. Via_Toyama_(2015)_Geek_Heresy_Pg252_Endnotes URL: https://psycnet.apa.org/record/2011-16843-000 Quotes: " Abstract When psychologists isolate the personal qualities that predict "positive outcomes" in life, they consistently find two traits: intelligence and self-control. So far researchers still haven't learned how to permanently increase intelligence. But they have discovered, or at least rediscovered, how to improve self-control. Hence this book. We think that research into willpower and self control is psychology's best hope for contributing to human welfare. (PsycINFO Database Record (c) 2017 APA, all rights reserved) ";
  • #157 …. Service science has come a long way in two decades…
  • #158 Automation as application of knowledge to get work done. Computer science increases capabilities, and economics measure the increase in productivity.
  • #159 BiblioI2008 IfM and IBM (2008) Succeeding through service innovation: A service perspective for education, research, business and government. Cambridge, United Kingdom: University of Cambridge Institute for Manufacturing. ISBN: 978-1-902546-65-0. [online at ism.eng.cam.ac.uk] URL https://www.ifm.eng.cam.ac.uk/uploads/Resources/080428cambridge_ssme_whitepaper.pdf Quotes: "Service systems1 are dynamic configurations of people, technologies, organisations and shared information that create and deliver value to customers, providers and other stakeholders. They form a growing proportion of the world economy and are becoming central to the way businesses, governments, families and individuals work. Innovation, a term applied almost exclusively to technologies in the past, is increasingly used in relation to service systems. Ideas of service are, of course, not new. However, the scale, complexity and interdependence of today’s service systems have been driven to an unprecedented level, due to globalisation, demographic changes and technology developments. The rising significance of service and the accelerated rate of change mean that service innovation is now a major challenge to practitioners in business and government as well as to academics in education and research. A better understanding of service systems is required. Many individual strands of knowledge and expertise relating to service systems already exist, but they often lie in unconnected silos. This no longer reflects the reality of interconnected economic activities which, for example, sees manufacturers of engineering products adopting service-oriented business models and health care providers learning lessons from modern manufacturing operations. Indeed, there are wide gaps in our knowledge and skills across silos. In response, Service Science, Management and Engineering (SSME), or in short Service Science, is emerging as a distinct field. Its vision is to discover the underlying logic of complex service systems and to establish a common language and shared frameworks for service innovation. To this end, an interdisciplinary approach should be adopted for research and education on service systems. Developing Service Science is no easy task; it not only requires intensive collaboration across academic disciplines but also a doubling of R&D investment in service education and research by governments and businesses. All stakeholders must start to engage each other and make plans for service innovation. For those responsible for creating a service innovation roadmap, this white paper provides a starting point to raise awareness."; “Service system: Service systems are dynamic configurations of resources (people, technology, organisations and shared information) that can create and deliver service while balancing risk-taking and value- cocreation. The dynamics are in part due to the ongoing adjustments and negotiations that occur in all systems involving people. People are the ultimate arbiters of value and risk in service systems (in part because people are legal entities with rights and responsibilities). Service systems are complex adaptive systems. They are also a type of ‘system of systems’, containing internal smaller service systems as well as being contained in a larger service system (see Stakeholder). They typically interact with other service systems via value propositions, which may form stable relationships in extended value chains or service networks (see Service networks). Formal service systems are legal entities that can create legally binding contracts with other service systems. Informal service systems cannot create contracts, though individual people within them may be able to do so.” “Service innovation: A combination of technology innovation, business model innovation, social- organisational innovation and demand innovation with the objective to improve existing service systems (incremental innovation), create new value propositions (offerings) or create new service systems (radical innovation). Often radical service innovation will create a large population of new customers (public education – students; patent system – inventors; money markets – small investors). Service innovation can also result from novel combinations of existing service elements. Examples of service innovation include: On-line tax returns, e-commerce, helpdesk outsourcing, music download, loyalty programs, home medical test kits, mobile phones, money market funds, ATMs and ticket kiosks, bar code, credit cards, binding arbitration, franchise chains, instalment payment plans, leasing, patent system, public education and compound interest saving accounts.” “SSME: Service Science, Management and Engineering (SSME), or in short Service Science, is an emerging field. It includes curricula, training, and research programs that are designed to teach individuals to apply scientific, engineering, management and design disciplines that integrate elements of computer science, operations research, industrial engineering, business strategy, management sciences, social and legal sciences, and others in order to encourage innovation in how organisations create value for customers and stakeholders that could not be achieved through such disciplines working in isolation.” “Systems and systems world view: Systems are dynamic configurations of entities (elements or components) that interact over time and result in outcomes (internal changes to entities and external changes to regions of the system and the system as a whole). The study of physical, chemical, biological, computational, cognitive, economic, legal, social, political, service or any other type of systems, typically begins with a statement of the entities, interactions and outcomes of interest. Reductionist science attempts to discover more fundamental building blocks out of which the entities of the system are composed (new architectures), often with the goal of finding simpler or more parsimonious explanations of observed variety. In complex adaptive systems, entities have life spans and the types of entities change over time in ways that are difficult to predict. Service Science studies the evolution of entities known as service systems, which interact via value propositions and result (normatively) in value-cocreation outcomes. Understanding the evolution may shed light on the shifts from social to economic, political to legal, and cognitive to computational systems. The shift seems to depend heavily on an increasing amount of shared information to solve motivation and coordination problems.“ “T-shaped professionals: Those who are deep problem solvers with expert thinking skills in their home discipline but also have complex communication skills to interact with specialists from a wide range of disciplines and functional areas (see also Adaptive Innovators).” “Transdisciplinary: Transcending, or extending beyond the knowledge of any existing disciplines. For example, symbolic reasoning and general systems theory are considered to be applicable to all disciplines and hence labelled as transdisciplinary knowledge.” BiblioS2021 Spohrer J (2021) Service innovation roadmaps and responsible entities learning. In ITM Web of Conferences 2021 (Vol. 38, p. 01001). EDP Sciences. URL: https://www.itm-conferences.org/articles/itmconf/pdf/2021/03/itmconf_iess2021_01001.pdf Quotes: "Abstract. Service-Dominant Logic (S-D Logic) and service science provide a way for innovators and learners to look at the world differently and thereby improve quality-of-life for people over time. The continued development of service science as an emerging transdiscipline will depend on developing better measurements and tools for understanding the past and future identities, reputations, values, goals, and strategies of entities interacting to achieve outcomes. For example, Service Innovation Roadmaps (SIRs) can be thought of as an at- tempt to make explicit the "learning investment strategy" of responsible entities (people, businesses, regional governments) to change and become "better future version of themselves" in terms of value co-creating service interactions. In short, SIRs can help with the challenge of upskilling people in an age of accelerating technology and policy changes. All service systems, as responsible entities learning, invest in three types of activities, herein termed Run- Transform-Innovate activities. This short paper provides context for a research direction to develop further the notions of SIRs and embrace complexity economics as a tool for advancing service science."
  • #161 So what? A challenge for future IEEE MetroXRAINE conference is to include research on the measurement of trust in many contexts. For those wondering what the common denominator is between service science and artificial intelligence – it is trust.
  • #162 But it is not just businesses, doing accelerated value co-creation, it is individual people too, in the X+AI era dawning. BiblioH2022 Hoffman R, Casnocha B (2022 [2012]) The Startup of You (Revised and Updated): Adapt, Take Risks, Grow Your Network, and Transform Your Career. Currency. URL: https://www.amazon.com/Start-up-You-Future-Yourself-Transform/dp/0307888908/ Quotes: "In this invaluable book, LinkedIn co-founder Reid Hoffman and venture capitalist Ben Casnocha show how to accelerate your career in today’s competitive world. The key is to manage your career as if it were a startup business: a living, breathing, growing startup of you. Why? Startups—and the entrepreneurs who run them—are nimble. They invest in themselves. They build their professional networks. They take intelligent risks. They make uncertainty and volatility work to their advantage. These are the very same skills professionals need to get ahead today. This book isn’t about cover letters or résumés. Instead, you will learn the best practices of the most successful startups and how to apply these entrepreneurial strategies to your career. Whether you work for a giant multinational corporation, stitch together multiple gigs in a portfolio career, or are launching your own venture, you need to know how to • adapt your career plans as pandemics rage and technologies upend industries • develop a competitive advantage so that you stand out from others at work • strengthen your professional network by building powerful alliances and maintaining a diverse mix of relationships • engineer serendipity that produces life-changing career opportunities • take proactive risks to become more resilient to industry tsunamis • tap your network for information and intelligence that help you make smarter decisions The career landscape has changed dramatically in the decade since Hoffman and Casnocha first published this guide. In an urgent update to the frameworks that have helped hundreds of thousands of people transform their careers, this new edition of The Startup of You will teach you how to achieve your boldest professional ambitions."; BiblioS2022 Spohrer J, Maglio PP, Vargo SL, Warg M (2022) Service in the AI Era: Science, Logic, and Architecture Perspectives. Business Expert Press. URL: TBD Quotes: "Are you prepared for the coming AI era? AI advances will profoundly change your daily service interactions, so this book provides readers with a necessary understanding of service, the application of resources (e.g., knowledge) for the benefit of another. In just minutes, you can learn about today’s use of early-stage AI for automation and augmentation, and essential elements of service science, service-dominant (S-D) logic, and Service-Dominant Architecture (SDA). Ultimately, improved service for all is possible with human-level AI and digital twins—but requires investing wisely in better models: Better models of the world both complex natural and social systems (science), better mental models in people to improve interactions (logic), better cultural and structural models of organizations to improve change (architecture), and better trusted and responsible AI models. The service innovation community studies and builds better models to improve interactions and change in business and society. The book challenges all responsible actors—individuals, businesses, universities, and governments—to invest systematically and wisely to upskill with AI (the X+AI vision). The service innovation community is a growing transdiscipline harnessing all disciplines to become better T-shaped professionals. Extensive end notes, bibliography, and index are provide.";
  • #163 Spohrer J, Siddike (2018) The Future of Digital Cognitive Systems: Tool, Assistant, Collaborator, Coach, Mediator. In Ed. Araya D. Augmented Intelligence: Smart Systems and the Future of Work and Learning. Peter Lang International Academic Publishers; 2018 Sep 28. Siddike MA, Spohrer J, Demirkan H, Kohda Y. A Framework of Enhanced Performance: People's Interactions With Cognitive Assistants. International Journal of Systems and Service-Oriented Engineering (IJSSOE). 2018 Jul 1;8(3):1-7. Rouse WB, Spohrer JC. Automating versus augmenting intelligence. Journal of Enterprise Transformation. 2018 Feb 7:1-21. Araya D. Augmented Intelligence: Smart Systems and the Future of Work and Learning. Peter Lang International Academic Publishers; 2018 Sep 28.
  • #164 Engelbart D. Augmenting human intellect. Summary report AFOSR-3223 under Contract AF. 1962 Oct;49(638):1024. Spohrer JC, Engelbart DC. Converging technologies for enhancing human performance: Science and business perspectives. Annals of the New York Academy of Sciences. 2004 May;1013(1):50-82. Licklider (1960) https://groups.csail.mit.edu/medg/people/psz/Licklider.html - focus scientists, engineers, etc. Me to Everyone (8:30 AM) Bush (1945) https://www.theatlantic.com/magazine/archive/1945/07/as-we-may-think/303881/ - as we may think Me to Everyone (8:30 AM) Engelbart (1962) started building it :-) https://web.stanford.edu/dept/SUL/library/extra4/sloan/mousesite/EngelbartPapers/B5_F18_ConceptFrameworkInd.html Bush and Licklider envisioned it Me to Everyone (8:31 AM) Bush and Licklider funded programs that benefitted Engelbart building it As people gain more powers (super-powers) - augmented capabilities - intelligence, physical strength, social interaction capabilities, perception, etc. - we need to become more responsible and wiser - these are the human-value aspects we discussed at HICSS panel that Ivy lead in Jan 2020. @Ivy - agreed. AI will be the greatest tool so far, to help us people understand ourselves better. We are already getting insights into human bias thanks to AI Trusted AI is so important that IBM continues to develop it and in open source - shared with the world, and benefitting from many collaborators - see Trusted AI at Linux Foundation AI & Data (I am TAC chair there) https://lfaidata.foundation/projects/trusted-ai/ please feel free to join our Slack discussion on open source AI at https://slack.lfaidata.foundation For Trusted AI and Responsible People - we have been developing at LF AI & Data - (RREPEATS - Reproducibility, Robustness, Explainability, Privacy, Equitability, Accountability, Transparency, Security)
  • #165 Kline SJ. Conceptual foundations for multidisciplinary thinking. Stanford University Press; 1995. Malone TW. Superminds: The surprising power of people and computers thinking together. Little, Brown Spark; 2018 May 15. Norman D. Things that make us smart: Defending human attributes in the age of the machine. Diversion Books; 2014 Dec 2. Spohrer JC. Information in places. IBM Systems Journal. 1999;38(4):602-28. Alan Kay & Steven Jobs - Bicycles for the mind (two types of IA) Don Norman – Thinks that make us smart Stephen J. Kline – Conceptual Foundations of Multi-Disciplinary Thinking Jim Spohrer – World Board (Augmented Reality – Perception Augmentation) Tom Malone – Super Intelligence
  • #168 Spohrer J, Golinelli GM, Piciocchi P, Bassano C (2010) An integrated SS-VSA analysis of changing job roles. Service Science. 2010 Jun;2(1-2):1-20. URL: https://pubsonline.informs.org/doi/pdf/10.1287/serv.2.1_2.1 This is a variation of James March’s work. He is the father of organization theory, and worked with Herb Simon in the 1950’s… March, J.G.  (1991)  Exploration and exploitation in organizational learning.  Organizatinal Science. 2(1).71-87. Every entity -- individual, enterprise (business and non-profit), city/region and nation that can change – makes a resource allocation decision…. Run is least costly and least risky if the environment is not changing much (change is gaining experience – practice effects and learning curves, anomaly detections) Transform is costly and risky, but may have benefits once the change is complete (adopting a new best practice) Innovate may be costly and risky, but also may create the greatest value, if the practices can be monetized if others adopt them (e.g., patents, consulting practices, etc.) FYI.... short history of transistors, integrated circuits, and data centers From transistors... 1. The transistor is considered by many to be the greatest technology invention of the 20th Century 2. While the concept of the transistor has been around since the 1920's (Canadian Physicist Julius Edgar Lilienfeld's 1925 Patent - devices that use physical phenomenon of field electronic emissions)... 3. Commercially available individual transistors that could be wired into circuits, invented and commercialized in 1947 & 1948 (Bell Labs Shockley Point Contact/Junction Transistor Theory 1947, Raytheon CK703 first commercially available 1948) To Integrated circuits... 4. However, it was not until the late 1950's and early 1960's that manufacturing process advances and commercial applications began using many of them in integrated circuits (TI, Bell Labs, etc.) - Sept 1958 the first integrated circuit (Jack Kilby TI) To Moore's law.... 5. By 1965 Gordon Moore's (Intel) paper stated the number of transistors on a chip would double about every two years (and exponential increase that has over 40 years of confirmation)... 6. The number of transistors manufactured each year (in 2009) is estimated at 10**18 - 3.9 x 10**6 transistors produced in 1957 (tenth anniversary of first transistor) - abut 10**18 transistors manufactured in 2009 (62th anniversary of first transistor) To data centers and "electricity consumption" .... 7. By 2005, data centers and server farms consume 0.5% of total worldwide electricity production (1% if cooling is included) - 2005 consumption equivalent of seventeen 1000 MW powerplants - electric consumption for data centers doubled from 2000 to 2005 Sources: http://semiconductormuseum.com/HistoricTransistorTimeline_Index.htm http://www.mentor.com/company/industry_keynotes/upload/rhines-globalpress-low-power.pdf http://www.iop.org/EJ/article/1748-9326/3/3/034008/erl8_3_034008.pdf?request-id=7cf4b6e5-498f-4ed4-bfc9-76eda96773ce
  • #169 APPLE https://podcasts.apple.com/us/podcast/service-science-and-the-impending-ai-revolution/id1612743401?i=1000583800244 SPOTIFY: https://open.spotify.com/episode/0n3h9rgX6UYDCwxgTzokoK?si=yVF0mtHsRZSmdfy-aMi8DA GOOGLE  https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy5idXp6c3Byb3V0LmNvbS8xOTQ5NTE3LnJzcw?sa=X&ved=2ahUKEwiPzL-Zxvv6AhXzjo4IHVbTAuUQ9sEGegQIARAC
  • #170 So what? Nott just disciplines and systems, but cultures are important. All disciplines are on a transdisciplinary journey. To be relevant. SSME+DAPP Diverse systems (a wide range of systems) include healthcare, education, government, finance, retail, hospitality, transportation, green energy, and more. Learning Systems invest in three types of activities Run-Transform-Innovate. Run = Routine Activities Transform = Copy Activities (of Others - Social Learning) Innovate = Discovery and Invention Activities (that others may want to copy – Societal Learning) T-shaped skills for people are needed in times of accelerating change. In times of slow change, I-shaped skills for people will work, but during times of accelerating change – it is better to have T-shaped skills for people who can be adaptive innovators, learning new areas faster and able to communicate with more people in large, diverse teams. BiblioS2008 Spohrer J, Kwan SK (2008) Service Science, Management, Engineering, and Design (SSMED): Outline and References. Trends and Perspectives. International Journal of Information Systems in the Service Sector (IJISSS). 1(3):1-31. URL: https://www.academia.edu/29743540/Service_Science_Management_Engineering_and_Design_SSMED_Outline_and_References?email_work_card=thumbnail-desktop Quotes: "Abstract - The growth of the global service economy has led to a dramatic increase in our daily interactions with highly specialized service systems. These daily service interactions are both frequent and diverse, and may include retail, financial, healthcare, education, on-line, communications, technical support, entertainment, transportation, legal, professional, government, or many other types of specialized interactions. We often play the role of customer in these interactions, but we also play the role of provider at home and work. The purpose of these many interactions is to create (or sometimes to mitigate the destruction of) value of some type. On those especially busy days of creating or salvaging value, we all come to realize, perhaps reluctantly at first, that we live, work, and play by taking on a great many roles in a great many service systems, and that we are all, in fact, individual service systems ourselves - increasingly complex, multitasking, highly specialized, knowledge-intensive human service systems - in ‘business’ to interact with others and co-create value. And yet surprisingly few students graduating from universities have studied anything about service systems. Service Science, Management, Engineering, and Design (SSMED), or service science for short, is an emerging discipline aimed at understanding and innovating service systems. Service systems are ancient, since the dawn of specialized knowledge and the division of labor, and are now rapidly evolving as costs plummet due to information and communication technologies (ICT) innovations that accelerate the creation of and sharing of specialized knowledge assets. Informal and formal service systems have been coevolving at an accelerating rate. Informal service systems depend more on traditional social systems and authoritative political systems (superordinate goal – which is why authority may appear “unfair”), and formal service systems depend more on monetary economic and strict adherence to legal system judgments (process without utility comparison – which is why bureaucracy may appear “unreasonable” or “out-moded’). Service systems exist and expand because of the value of the growing body of specialized knowledge assets distributed across a growing population of specialized people, and because of the mathematical advantages of dependent win-win value co-creation (value propositions) and collective-win (governance mechanisms) interactions over purely independent ‘do-it-all-myself” activities. Service systems (normatively) co-create value by applying specialized knowledge of diverse capabilities (provider perspective) and reciprocal needs (customer perspective) as they interact with and establish relationships or one time encounters with other service systems. This paper sketches an outline and preliminary set of references to provoke discussions about the difficult challenge of integrating multiple disciplines to create a new and unique service science. The sketch outlines the theoretical and practical foundations of the emerging field of service science, as well as the types of expertise (both broad interactional and deep contributory) that are important to service science professionals. Service science professionals seek to create and improve service systems (and their associated value propositions, governance mechanisms, and service networks). A service science lab network is also described, that could someday provide real, virtual, and simulated world experiences to educate and provide practical work experiences for future service scientists, and students of other disciplines seeking a better understanding of service systems as well.” BiblioS2016 Spohrer J, Bassano C, Piciochhi P, Siddike MAK (2016) What Makes a System Smart? Wise? URL: Quotes: "Abstract - The human-side of service engineering community has an opportunity to participate in an emerging trend to connect sociotechnical system research and engineering with the DIKIW (data-information-knowledge-intelligence-wisdom)hierarchy. The digital economy is grounded in big data and information systems.The knowledge economy is being redefined in the cognitive era by artificial intelligence, machine learning, and natural language processing capabilities, and asa result our systems are getting more intelligent or smarter. However, beyonds smarter, what are wiser systems? Can these terms be made more rigorous and operational? The goal of this paper is to provide a jumping off point for the AHFE HSSE community on this topic, and to explore the concept of smart versus wise from three related socio-technical systems perspectives: polycentric systems, viable systems, and service systems. Keywords Polycentric systems, Viable systems, Service systems, Smart systems, Wise systems, Human-side of service engineering"; "Service Science - To integrate service-related concepts across discipline boundaries, the concept of service system has been proposed as the basic abstraction for the emerging service science community [21]. Service science is short for Service Science Management Engineering Design Arts and Public Policy (SSME+DAPP) [22, 23]. Service science studies and seeks to integrate concept from many disciplines that study the global evolving ecology of nested networked service system entities, and their value co-creation and capability co-elevation interaction [24]. Within service sci- ence, governance mechanisms are one type of value proposition that can guide entity interactions [25]. The ISPAR model proposed in service sciences specifies both service and non-service modes of interaction and outcomes for entities, and the possibility of disputes and need for dispute resolution mechanisms [21]."
  • #171 As universities become better partners with their host city, the innovations centers are strengthened and faculty and students get streams of data from different city systems from transportation, to water and waste, to healthcare, and energy systems…. Students learn to work on multidisciplinary teams and engage in understanding and creating proposed solutions to real-world problems that do not respect discipline boundaries – in this way students are better prepared to become good citizens in their future community, and to work on multidisciplinary teams when they graduate and get jobs… Urban Innovations Center are related to Urban Planning departments. However, Urban Planning tends to focus on land use and development, whereas Urban Innovations Centers are emerging with broader agendas…
  • #172 Top 3000 cities: http://www.mongabay.com/cities_pop_02.htm Of course the opportunity is not just local – while local innovation impact the lives of staff, faculty, students and their families most directly – as cities partner more (twin city and sister city programs) and as universities also establish global collaborations with campuses in other regions of the world – the opportunity for better city-university partnerships is both local and global.