The document discusses the role of AI, service systems, and the importance of upskilling in a rapidly changing technological landscape. It highlights Jim Spohrer's career experiences and contributions to AI and education, including insights on productivity, innovation, and the emergence of AI-operated roles. Additionally, it touches on societal implications, such as legal personhood for natural features and the evolving interaction between humans and AI systems.

1. Truth & Service in the AI Era
Thanks to Tor Andreassen and Marina Gorbis
for the opportunity to share some thoughts
January 13, 2025
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
X/Twitter: @JimSpohrer
LinkedIn: https://www.linkedin.com/in/spohrer/
Slack: https://slack.lfai.foundation
Slack: https://issip.slack.com
2001 2015 2021 2022 2023 2024

2. 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

5. TheNeuron

7. 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
)
Cost of computation goes down by 1000x every 20 years (left to right diagonals), driving knowledge worker productivity up.

8. 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!)

9. 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!)

12. Gartner Predicts Power Shortages Will Restrict 40% of AI
Data Centers By 2027
https://www.gartner.com/en/newsroom/press-releases/2024-11-12-gartner-predicts-power-shortages-will-restrict-40-percent-of-ai-data-centers-by-20270

13. “NorthPole Chip”
Far less energy.

14. Impressive, but imperfect
Physical realm: Energy
Technical realm: Mistakes (”Hallucinations”)
Social realm: Digital property theft

15. 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

16. 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.”
ervice Systems and AI
AI Tools
in coming
decades…

18. 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

19. Self-Control

20. 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

21. • 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)

22. Innovation Professionals (ISSIP.org)
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.

23. 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

24. Thank-you for
participating today!
You are all awesome!!

25. •https://youtu.be/PnmVqASd1VE
Lee Nackman (retired IBM) – Thinking
AI

26. 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

27. 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

28. Important
Distinctions

29. • Jim Twin V1: My papers -> short talk videos
• English
• French
• How to stay future ready?
• Learn the building blocks
• Plot your influencers (refresh regularly)
• 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

30. 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)

31. 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!!!

32. 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.

33. 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.

34. 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

35. Route 128, aound Boston, MA USA
ICASSP 1983

36. We
Would
Love
Your
Voice https://www.jstor.org/stable/1747731

37. 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

38. 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

39. 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

40. 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

41. 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

42. 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

43. 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

44. Today’s Talk: Topics for discussion
• Past
• 1947, 1958, 1971
• Present
• 70, 35000, 250000
• Future
• TBD

45. 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

46. 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

47. • 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

48. MORE SPOHRER USE CASES:
https://service-science.info/archives/6521

49. 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
pohrer

50. http://www-formal.stanford.edu/jmc/history/dartmouth/dartmouth.html https://cdn.openai.com/papers/gpt-4.pdf
1955 2023

51. 1960 1980 2000 2020 2040 2060 2080
Time

52. 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

53. 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)

54. 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).

55. 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
)
Cost of computation goes down by 1000x every 20 years (left to right diagonals), driving knowledge worker productivity up.

56. 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!)

57. 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!)

60. “NorthPole Chip”
Far less energy.

61. Impressive, but imperfect
Physical realm: Energy
Technical realm: Mistakes (”Hallucinations”)
Social realm: Digital property theft

62. • 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

63. Backup Slides
Template slides and others

64. Topics for Discussion
• Beyond Language for Communications
• Here is how my AI, using my digital twin of you, predicted that you would respond to my request
– could you please ask your digital twin of yourself to check this response and suggest
improvements?
• How to keep up with accelerating change?
• Who do you follow? What two main dimensions do you try to balance? Hype-buster <-> Super-
Optimist, Doing (Try this) <-> Knowing (News)
• How to verify results of generative AI?
• How to deal with verification challenge? Run Open AI ChatGPT 3.5, Google Bard (waiting for
Gemini), Anthopic’s Claude, Microsoft Bing power by Open AI ChatGPT 4 – in parallel and have
them critique each others’ responses (where they agree, where and how they differ) – if possible,
also run Meta and open source to compare (Generate-Test-and-Debug)
• How to deeply understand how generative AI works?
• Monkey’s at the typewrite in high dimensional spaces that map to low dimensional spaces
• One dimensional space is time – what comes next? (Predictors, unsupervised learning)
• Two dimensional space is what people gravitate towards in business schools (Sorters, supervised
learning)

65. Today’s talk
• 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…
pohrer

66. Predict the Timeline: GDP/Employee
National Academy - Service Systems and AI 66
(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

67. ognitive Systems
Types: Progression of Models : Verified, Trusted, Wise
Models = instruction_set of future: Better building blocks
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

68. 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.
Part 3: “Solving All Problems”

69. Thank you