The document outlines a discussion on T-shaped skills, AI strategies, and service science taking place in Brno, Czech Republic from February 5-9, 2024, involving contributions from industry experts including retired IBM executive Jim Spohrer. It emphasizes the importance of intelligence augmentation in improving service systems while addressing stakeholder concerns and the need for upskilling in a technology-driven environment. The discussion also covers the impact of open-source software in the digital economy and future projections of service innovation and university-driven collaboration.

1. Brno, Czech Republic
(1) Universities & T-shaped Skills
(2) Businesses & AI /IA Strategies
(3) Cities/Humanity & Service Science
Thanks Leonard Walletzky and Michele Leonard
To discuss T-shaped skills, AI/ IA strategies, service science
February 5-9, 2024 in Brno, Czech Republic
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. Thank-you!

3. Today’s talk
• Service Science and Intelligence
Augmentation: Past, Present, and Future
Research Questions.
• This talk explores the past, present, and
possible futures of amplifying the capabilities
(including intelligence augmentation) of
service systems entities (co-elevation of
capabilities), and the research questions
related to rapidly scaling benefits, while
simultaneously (1) mitigating harms to
stakeholders and underserved populations,
as well as (2) upskilling people and
organizations learning to invest wisely and
systematically in improved win-win
interaction and change. AI can help achieve
a transdisciplinary research approach
2010

4. In Memory of Douglas Engelbart (1925-2013)

5. 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
2/7/2024 Jim Spohrer (ISSIP) 5
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)

6. Past
• Economics – Service Sector Productivity

7. IBM’s Service Journey: A Summary Sketch
Jim Spohrer (ISSIP) 7
Spohrer J (2017 ) IBM's service journey: A summary sketch. Industrial Marketing Management. 60:167-172.
9/2/22

8. What expertise does
a service scientist require?
What degrees can
a service scientist earn?
Ultimately, what tool will
a service scientist most need?
Ultimately, what purpose should
a service scientist focus on?
How to invest wisely?
Year Delighted when… … and many people to thank when…
2024 IESS in Brno, Cech Republic
2023 Generative AI , Humanoid Robots, nd AI Digital Twins of Service
System Entities
2022 Exploring ServCollab and ISSIP collaborations. NAE Event on SSME in AI
Era and T-shaped Skills mentioned in Nick Donofrio Autobiography
2021 Christopher Lovelock Career Contributions to Service Discipline Award
IBMer Utpal Mangla, Elected to 2022 ISSIP VP/2023 President role
2020 Linux Foundation AI & Data TAC Chair Elected – open-source trusted AI
2019 Handbook of Service Science, Volume 2
2018 IBMer Rama Akkiraju, President of ISSIP
2017 Daniel Berg Award for Technology and Service Systems Award (IAITQM)
2016 NSF invests $13M in smart, human-centered Service Systems
2015 IBMer Jeff Welser, President of ISSIP
2014 IBM hosted Frontiers in Service Conference in San Jose, CA
2013 Vargo & Lusch S-D Logic Award, E. Gummesson Award (Naples Forum)
PICMET Fellow for Advancing Service Science
2012 International Society of Service Innovation Professionals established
2011 IBM Centennial Icon-of-Progress – including SSME and Smarter Planet
2010 Handbook of Service Science, Volume 1
2009 Robin Qiu launches INFORMS Journal of Service Science
2008 Cambridge Report – “Succeeding Through Service Innovation”
HICSS starts a service scince mini-track Paul Maglio/Furen Lin
2007 SSME in USA America COMPETES Act Congressional Legislation
IBM hosted Frontiers in Service Conference in San Francisco, CA
2006 IBM Research Awards for CBM, Data Analytics, Solution, etc. tools
2005 Attended fist Frontiers in Service – ”Big tent” getting bigger
2004 China, Japan, Finland, Germany, etc. Launch knowledge-intensive
service initiatives
2003 ”Big Tent” Service Conference at IBM Almaden, SSME Faculty Awards
2002 IBM established Almaden Service Research (ASR) group

10. Holistic Service Systems (HSS)
2/7/2024 Brno, Czech Republic (Feb. 5-9, 2024) 10
http://www.service-science.info/archives/1056
Nation
State/Province
City/Region
University
College
K-12
Cultural &
Conference
Hotels
Hospital
Medical
Research
Worker
(professional)
Family
(household)
For-profits:
Business Entrepreneurship
Non-profits
Social Entrepreneurship
U-BEE
Job Creator/Sustainer
U-BEEs = University-Based Entrepreneurial Ecosystems
“The future is already
here (at universities),
it is just not evenly
distributed.”
“The best way to
predict the future
is to (inspire the next
generation of students
to) build it better.”
“Multilevel nested,
networked
holistic service
systems (HSS)
that provision
whole service (WS) to
the people inside them.
WS includes
flows (transportation,
water, food, energy, communications),
development (buildings,
retail ,finance, health,
education),
and governance (city,
state, nation). ”
University Four Missions
1. Learning
2. Discovery
3. Engagement
4. Convergence

11. 11
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
water & waste transportation
health
energy/grid
e-government
food &
supply chain

12. 12
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)

13. Principle 5: Dynamics (Revisited)
2/7/2024 (c) 2014 IBM UP (University Programs) 13

14. Principle 5: Dynamics
2/7/2024 (c) 2014 IBM UP (University Programs) 14

15. Service Systems Engineering in the Human-Centered AI Era 15
Value
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

16. Present
• Technology – Top Ten Market Cap Companies
• Competition
• Digital Transformation

18. Nations

19. Businesses

20. People

23. Gandhi P, Khanna S, Ramaswamy S (2016)
Which Industries Are the Most Digital (and Why)?
Harvard Business Review
URL https://hbr.org/2016/04/a-chart-that-shows-which-industries-are-the-most-digital-and-why

24. • Summary. Free and open source
software (FOSS) is essential to much of
the tech we use every day — from cars
to phones to planes to the cloud. While
traditionally, it was developed by an
army of volunteer developers and given
away for free, companies are
increasingly taking a more active role in
its development. But as companies buy
up open source companies, bring
development in house, and spin off their
own for-profit versions of FOSS
products, they could be endangering the
future of this essential software. To
maintain the viability and security of
FOSS, companies should: 1) have a clear
policy towards open source —
preferably one that encourages
employees to contribute to FOSS if
feasible, 2) raise their level of awareness
about the FOSS that they use and stay
apprised of its vulnerabilities, and 3)
keep the stability of the software they
use in mind and incentivize their
employee contributions to focus on both
features useful to the company as well
as general security and maintenance.
Lifshitz-Assaf H, Nagle F (2021) The Digital Economy Runs on Open Source.
Here’s How to Protect It. Harvard Business Review.
September 2, 2021
URL: https://hbr.org/2021/09/the-digital-economy-runs-on-open-source-heres-how-to-protect-it

25. Future
• Better Models of the World (Holistic Service Systems Thinking)
• Decarbonized Energy (Incremental, Radical, Super-Radical)
• Self-Control (Heart, Mind, Will) – Toyama (2015) “Geek Heresy”
• Competing for Collaborators

26. Eleven (11) levels – order of magnitude observation
Service system entities that get and give service.
Service is the application of resources (e.g., knowledge) for the benefit of another.
Ref: SDL
Ref: Spohrer,, Kwan, Fi

27. Seeing the world differently

28. 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 28
AI Tools
in coming
decades…
2/7/2024

29. 2/7/2024
The International Society of Service Innovation Professionals
(ISSIP.org)
29

30. 2/7/2024
The International Society of Service Innovation Professionals
(ISSIP.org)
30

31. 2/7/2024
The International Society of Service Innovation Professionals
(ISSIP.org)
31

32. 2/7/2024
The International Society of Service Innovation Professionals
(ISSIP.org)
32

33. 1960 1980 2000 2020 2040 2060 2080
Estimation Framework (Time)

34. 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
Estimation Framework (Cost)

35. 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
Estimating Cost of Computation

36. 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
Estimating Cost of Computation
Note: Adjust Kilo and Mega scales slightly to fit data better.

37. 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
Estimating Human-scale Comparison
Human-scale
Brains Compute
One Exa- (1018)
Billion Ronna- (1027)

38. 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
GDP/Employee
Trend
Estimating Knowledge Worker Productivity
Based on USA
Historical Data
Year Value
1960 $10K
1980 $33K
2000 $78K
2020. $151K
2023 $169K

39. Estimating Knowledge Worker Productivity

40. 40
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!)

41. 41
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!)

42. Innovation
• Incremental
• New Value(s) – Existing Unit(s)
• Example: Vehicles Kilometers/Kilowatt-Hour (Transportation)
• Radical
• New Value(s) – New Combination(s) of Existing Unit(s)
• Example: Smartphones Bits/Joule (Communications)
• Super-Radical
• New Value(s) – New Combination(s) with New Unit(s)
• Example: Goal-level of what percentage of the population, Online Commerce
Trust/Future Prediction Accuracy (Computation); Mtrans. Exploration &
Learning.

43. 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

44. Who I am: Take 2
The Three Ages of Man (Giorgione)
Thanks to Alan Hartman for kind inspiration (slides) (recording)
Service is an actor applying resources (e.g., knowledge) to benefit another
Service system entities are responsible actors that give and get service
(e.g., people, businesses, universities, nations, etc.)
Service science studies service systems as an evolving ecology
of responsible actors that interact and change.
Service innovations improve win-win interaction and change
in business and society
Service systems are dynamic configurations of four types of resources
2/7/2024 Jim Spohrer (ISSIP.org) 44
Environmental and ecological sciences
ServCollab

45. 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. We get the future we invest in – so invest wisely.
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)

46. Preamble: On Value
• Service Science
• S-D Logic (Vargo & Lusch 2016)
• Service is the application of resources (e.g.,
knowledge) for the benefit of another
• Value … uniquely … determined by beneficiary
• Improvement processes for service system
innovation and value cocreation
• Learning to invest systematically to…
• Improve win-win interaction
• Improve win-win change
• Businesses as service systems
• Technology platforms, energy, investing, healthcare
• Nations as service systems
• Investments in upskilling people
• Top ranked global universities
• Population (+ capital-technology-wealth)
• A Brief History of Value
• Family (GDP of tribes)
• Cities (GDP of cities)
• Nations (GDP of nations)
• Businesses (GDP of AI-powered platforms that help
people interact, upskill, upenergy, upwealth,
uphealth, etc.)
Value cocreation is accelerated when large numbers of highly skilled people with advanced technology have a safe, ethical, and sustainable environment for win-win interaction and change.
Jim Spohrer (ISSIP) 46
9/2/22

47. Estimating Knowledge Worker Productivity
• Estimation Framework (Time and Cost)
• Draw seven vertical lines, label them with year from 1960 to 2080
• Draw five horizontal lines, label them with dollars from $1 to $Trillion
• Estimating Cost of Computation
• Add horizontal lines – that is Moore’s Law – cost of computation as a function of
time from Kiloscale (103) to Ronnascale (1027)
• Estimating Human-Scale Comparison
• Make Exascale (1018) thicker – estimated computing power of 1 person’s brain
• Make Ronnascale (1027) thicker – estimated computing power of a billion brains
• Estimating Knowledge Worker Productivity
• Add GPD/Employee in USA – that is an estimate of knowledge worker productivity

48. 2/7/2024 Jim Spohrer (ISSIP.org) 48
(Chorus)
AI, AI, enhancing the way,
Personalization brightens each day.
With tailored recommendations, it's clear,
SIR members' interests, AI holds dear.
Oh, SIR, SIR, hear this tune so true
ChatGPT Prompt: Please transform
the essay “AI for SIR members” into a song
to the tune of "Daisy, Daisy give me
your answer do”
DALL-E Prompt: Generate a painting
of the essence of technology and camaraderie
with a vibrant and engaging image of retired men
singing together. Evoke a sense of excitement and
showcase the power of AI in enhancing the lives of
SIR members.

49. Let’s level set – how many of you know about…
Ethan Mollick (UPenn Wharton) Don Norman (UC San Diego)
Scott Pelley (CBS, 60 Minutes)
Tristan Harris and Aza Raskin
(Center for Humane Technology) Generative AI Tools
To Output:
Text/Writing
Images
Code/Programming
Videos
Audio
Music
Game Worlds
Digital Twin
Other?
2/7/2024 Jim Spohrer (ISSIP.org) 49

50. 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…
2/7/2024 Jim Spohrer 50

51. Today’s Talk
• Transforming Businesses, Industries, and
Governments: What is the "Best" Service System
Ecology Strategy in the AI Era?
• Businesses historically have profited by either
becoming innovation leaders or fast followers, in both
domestic and global markets, while simultaneously
becoming the keystone of their ecosystem - the prize for
innovators and new market makers. However, winner-
take-all and improve-weakest-link strategies are on the
verge of being redefined in the AI era of unprecedented
accelerating change. AI can help achieve Z2B (zero to a
billion) for smaller and smaller teams across a wider and
wider array of metrics, financial and others. AI digital
twins can help people both (1) to keep up with
accelerating change and (2) to achieve a more humanity-
centered approach to business and government.

52. 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)
2/7/2024 Jim Spohrer 52

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

54. Narrow AI
Emerging
Broad AI
Disruptive and
Pervasive
General AI
Revolutionary
▼ We are here (2023)
2050 and beyond 54
IBM Research AI © 2018 IBM Corporation
The evolution of AI
Borrowed from David Cox, IBM-MIT Lead
▼ We were here (2018)
▼ Alan D Thompson
AGI prediction (2025)

55. Predict the Timeline: GDP/Employee
National Academy - Service Systems and AI 55
(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

56. Types: Progression of Models : Verified, Trusted, Wise
Models = instruction_set of future: Better building blocks
2/7/2024 Understanding Cognitive Systems 56
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

57. Resilience:
Rapidly Rebuilding From Scratch
• Dartnell L (2012) The Knowledge: How to
Rebuild Civilization in the Aftermath of a
Cataclysm. Westminster London: Penguin
Books.
2/7/2024 Jim Spoihrer (ISSIP) 57
Part 3: “Solving All Problems”

58. 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!

59. 2012

60. 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

63. “NorthPole Chip”
Far less energy.

64. First “Milk” Beer
(Mostly Foam)
Brno, Czech Republic
Feb. 4, 2024

65. 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

66. 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
GDP/Employee
Trend
Estimating Knowledge Worker Productivity
Based on USA
Historical Data
Year Value
1960 $10K
1980 $33K
2000 $78K
2020. $151K
2023 $169K
Cost of computation goes down by 1000x every 20 years (left to right diagonals), driving knowledge worker productivity up.

67. T-Shaped Professionals
• Title: Preparing T-Shaped Professionals for Career
Success in the AI Era
• Speaker: Jim Spohrer
• Abstract: As universities transform curriculum in the AI
era, the importance of preparing T-shaped
professionals for career success is an important topic to
explore. T-shaped professionals have deep disciplinary
problem-solving skills and broad communications skills
for improved teamwork and rapid learning of new
areas. T-shaped professionals have depth and breadth
across six areas: Emerging technologies, work practices,
developmental mindsets, academic disciplines, societal
systems, regional cultures. This talk will provide an
overview of the past, present, and future of the T-
shaped skills concept, with special attention to possible
applications in Informatics curriculum development.

68. Anthropic Claude-2: Please create a 5 minute
talk for a university Informatics faculty
audience based on this title, speaker, and
abstract
• Here is a 5 minute talk on preparing T-shaped professionals for career success in the AI era:
• Good afternoon, everyone. I’m Jim Spohrer from ISSIP, the International Society of Service Innovation Professionals. Today, I’d like to have a conversation about the importance
of developing T-shaped professionals as we continue transforming curriculum in this era of artificial intelligence.
• As a quick refresher, the concept of the T-shaped professional emphasizes both deep disciplinary expertise, the vertical stem of the “T”, as well as broad communication and
collaboration abilities, the horizontal top of the “T”.
• There are compelling reasons why this T-shaped model is critical for preparing students’ career success today. Discipline-specific technical skills alone are vulnerable in a world of
AI and automation. Students also need adaptability in learning new areas, working across disciplines, understanding social contexts, and more. T-shaped capabilities build this
agility.
• Concretely, T-shaped professionals have depth and breadth across six dimensions relevant to the AI era and the digitally driven world: emerging technologies, new work practices,
developmental mindsets, academic disciplines beyond one’s own, societal systems in industry and regionally, and finally, an empathy for diverse cultures.
• Now, in terms of Informatics curriculum, there are abundant opportunities to embed T-shaped skill-building. Experiential learning working with domain experts beyond computer
science, communication-intensive assignments addressing real user needs, ethics and social impact modules – these all foster T-shaped growth.
• As we strive toward curriculum that best equips students for long-term success, I welcome your perspectives on where infusion of T-shaped professional preparation shows
special promise and how we can promote these key meta-skills. Please feel free to find me afterwards if you have curriculum design ideas to discuss further!

69. Google Bard: Same prompt
• Introduction:
• Good morning, Informatics faculty! As the landscape of our world is fundamentally reshaped
by Artificial Intelligence, universities face a pivotal question: How do we prepare our
students for success in this dynamic era? Today, I want to introduce you to the concept of
the T-shaped professional, a model that equips graduates with the optimal blend of
specialized skills and adaptable mindset for enduring success in the AI era.
• The "T" Explained:
• Imagine the capital letter "T". The vertical bar represents deep expertise in a specific field
like Informatics. This includes robust programming skills, data analysis prowess, and a
strong understanding of core computational principles. But expertise alone isn't enough. The
horizontal bar of the "T" symbolizes broad, transferable skills, including:
• Communication: Articulating complex technical concepts to diverse audiences, both
technical and non-technical.
• Collaboration: Working effectively in teams, leveraging individual strengths, and resolving
conflicts constructively.
• Critical Thinking: Analyzing problems from multiple angles, identifying underlying
assumptions, and developing innovative solutions.
• Problem-Solving: Approaching challenges systematically, using data and evidence to reach
informed conclusions.
• Adaptability: Embracing lifelong learning, readily acquiring new skills, and thriving in an
ever-evolving landscape.
• Cultural Awareness: Understanding diverse perspectives, appreciating different working
styles, and fostering inclusive communication.
• Why T-Shaped Professionals Thrive:
• In the AI era, automation will handle routine tasks, leaving space for human ingenuity and
collaboration. T-shaped professionals excel in this environment because they can:
• Complement AI: Bring human judgment, creativity, and empathy to tasks where AI falls
short.
• Bridge the Gap: Translate technical concepts for non-technical stakeholders, fostering
collaboration and innovation.
• Navigate Change: Continuously learn and adapt, remaining relevant in a rapidly evolving job
market.
• Six Key Areas for Informatics Professionals:
• Beyond traditional technical skills, a well-rounded T-shaped Informatics professional
cultivates depth and breadth in six key areas:
1. Emerging Technologies: Understanding AI, machine learning, blockchain, and their
impact on various industries.
2. Work Practices: Adapting to remote work, agile methodologies, and data-driven
decision making.
3. Developmental Mindsets: Embracing continuous learning, seeking feedback, and
readily exploring new challenges.
4. Academic Disciplines: Recognizing the value of interdisciplinary approaches, drawing
insights from fields like psychology, sociology, and business.
5. Societal Systems: Understanding the ethical implications of AI, its impact on jobs, and
its role in building a more equitable society.
6. Regional Cultures: Appreciating diverse cultural perspectives and fostering inclusive
communication in global teams.
• The Future of T-Shaped Professionals:
• As universities adapt their curriculum, integrating the T-shaped model offers several
possibilities:
• Interdisciplinary courses: Combining technical with communication, humanities, or
social science courses.
• Project-based learning: Encouraging real-world problem solving and team
collaboration.
• Mentorship programs: Connecting students with industry professionals who embody
the T-shaped ideal.
• Conclusion:
• Embracing the T-shaped professional model equips our Informatics graduates with the
tools they need to not only survive but thrive in the AI era. By fostering both deep
expertise and broad adaptability, we empower them to become effective
communicators, collaborative problem solvers, and lifelong learners, shaping the future
of technology with human-centered ingenuity.
• Thank you!
• Note: This talk is approximately 4 minutes and 30 seconds long. You can adjust the
pacing and add additional details depending on your specific audience and desired
time frame.

70. OpenAI ChatGPT – same prompt.
• [Slide 1: Title Slide] Title: Preparing T-Shaped Professionals for Career Success in the AI Era Speaker: Jim Spohrer
• [Slide 2: Introduction] Good [morning/afternoon/evening], everyone! I am thrilled to be here today to discuss a topic that is of utmost importance in the rapidly evolving landscape of academia and
industry. Today, we're going to delve into the concept of "Preparing T-Shaped Professionals for Career Success in the AI Era."
• [Slide 3: About Jim Spohrer] But first, let me introduce myself. I'm Jim Spohrer, and I've spent a significant part of my career exploring the intersection of technology, education, and innovation. Today,
I'm excited to share insights on the transformation of university curricula in the context of the AI era.
• [Slide 4: Abstract Overview] Our focus today is on T-shaped professionals—individuals who possess deep disciplinary problem-solving skills along with broad communication skills. We'll explore how
these skills contribute to improved teamwork and rapid learning in new areas, especially in the context of emerging technologies.
• [Slide 5: The T-Shaped Professional] So, what exactly is a T-shaped professional? Imagine the letter "T." The horizontal bar represents a broad set of communication and interdisciplinary skills, while
the vertical stem embodies deep disciplinary problem-solving skills. T-shaped professionals are those who combine both breadth and depth in their skill set.
• [Slide 6: The Six Dimensions of T-Shaped Skills] Now, let's delve into the six dimensions of T-shaped skills: emerging technologies, work practices, developmental mindsets, academic disciplines,
societal systems, and regional cultures. T-shaped professionals possess depth and breadth across these crucial areas.
• [Slide 7: Past, Present, and Future of T-Shaped Skills] Next, we'll take a journey through the past, present, and future of the T-shaped skills concept. We'll explore its historical context, its relevance in
today's rapidly changing world, and the anticipated applications in the future, particularly in the field of Informatics.
• [Slide 8: T-Shaped Skills in Informatics] Now, how do T-shaped skills apply to Informatics? As universities transform their curricula, it's essential to integrate these skills into the education of future
professionals in this field. T-shaped skills can enhance problem-solving abilities, foster innovation, and prepare students for the dynamic challenges posed by AI.
• [Slide 9: Applications in Curriculum Development] Let's dive deeper into how T-shaped skills can be applied in Informatics curriculum development. We'll discuss practical strategies for incorporating
depth and breadth across various dimensions, ensuring that students graduate not only as specialists in Informatics but also as well-rounded professionals.
• [Slide 10: Q&A] As we wrap up, I want to open the floor to your questions and thoughts. I believe that a collaborative discussion is essential for embracing the T-shaped skills paradigm and preparing
the next generation of professionals for success in the AI era.
• [Slide 11: Thank You] Thank you for your time and attention today. I look forward to continuing the conversation and working together to shape the future of education and professional success in the
exciting era of artificial intelligence.
• [End of Presentation]

71. Microsoft Bing Copilot – same prompt
• Certainly! Here’s a 5-minute talk on “Preparing T-Shaped
Professionals for Career Success in the AI Era”:
• Preparing T-Shaped Professionals for Career Success in the AI
Era
• Introduction
• Ladies and gentlemen, esteemed faculty members, and fellow
students, thank you for joining me today. I am honored to discuss a
topic that lies at the intersection of education, technology, and
career readiness: T-shaped professionals. Specifically, we’ll
explore how universities can equip students with the right skills to
thrive in the ever-evolving landscape of artificial intelligence (AI).
• The AI Era: A Transformative Shift
• As universities adapt their curricula to the AI era, we find ourselves
in a transformative shift. AI technologies are reshaping industries,
automating tasks, and creating new opportunities. But success in
this era requires more than just technical prowess. It demands a
holistic approach—one that combines depth and breadth of skills.
• The T-Shaped Professional
• Depth: Disciplinary Problem-Solving Skills
• The vertical bar of the “T” represents depth. It signifies specialized
knowledge within a specific discipline. In our case, Informatics. Our
students must master algorithms, data structures, machine
learning, and other core concepts. This depth allows them to tackle
complex problems head-on.
• Breadth: Communication and Collaboration
• The horizontal bar of the “T” represents breadth. T-shaped
professionals possess broad communication skills. They can
collaborate across disciplines, bridging gaps between technical
experts, business leaders, and end-users. Effective teamwork is
essential for innovation.
• The Six Dimensions of T-Shaped Skills
• Let’s delve into the six areas where T-shaped professionals excel:
1. Emerging Technologies: Our students must stay abreast of AI advancements,
blockchain, quantum computing, and more. They should be curious, adaptable, and
ready to embrace change.
2. Work Practices: Understanding agile methodologies, design thinking, and project
management is crucial. How do we apply AI in real-world scenarios? How do we
iterate and improve?
3. Developmental Mindsets: T-shaped professionals cultivate a growth mindset.
They learn continuously, unafraid of failure. Resilience and adaptability are their
allies.
4. Academic Disciplines: Beyond Informatics, they appreciate the
interconnectedness of fields. AI intersects with ethics, psychology, economics, and
law. Our students must engage with these diverse perspectives.
5. Societal Systems: AI impacts society profoundly. Privacy, bias, and ethical
considerations matter. T-shaped professionals understand the broader implications
of their work.
6. Regional Cultures: Context matters. Whether working globally or locally, our
students must navigate cultural nuances. Empathy and cross-cultural competence
are essential.
• Applications in Informatics Curriculum
• How can we apply T-shaped skills in our Informatics programs?
1. Interdisciplinary Projects: Encourage collaboration across departments. Let
computer science students team up with business majors to solve real-world
problems.
2. Communication Training: Develop courses that enhance communication skills.
Writing, presenting, and active listening are vital.
3. Ethics and AI: Infuse ethics discussions into our curriculum. How do we ensure
fairness, transparency, and accountability in AI systems?
• Conclusion
• In conclusion, the T-shaped professional is not a mere metaphor—it’s a blueprint
for success. As we prepare our students for the AI era, let’s nurture both depth and
breadth. Let’s create graduates who can code algorithms and articulate their
impact. Let’s shape professionals who thrive in complexity, collaborate seamlessly,
and drive positive change.
• Thank you, and may our students become the architects of an AI-powered future!
🌟🤖🔍

72. Microsoft Bing Copilot - Image

73. -10
-5
0
5
10
15
1969 1974 1979 1984 1989 1994 1999
Levy, F, & Murnane, R. J. (2004). The New Division of Labor: How
Computers Are Creating the Next Job Market. Princeton University Press.
Expert Thinking
Complex Communication
Routine Manual
Non-routine Manual
Routine Cognitive

75. The ME in the T: Can-Do Attitude

76. 2/7/2024
© IBM 2015, IBM Upward University Programs Worldwide
accelerating regional development
76

77. Next Generation:
Future-Ready T-Shaped Adaptive Innovators
Many disciplines
Many sectors
Many regions/cultures
(understanding & communications)
Deep
in
one
sector
Deep
in
one
region/culture
Deep
in
one
discipline

79. Future-Ready T-Shapes
2/7/2024
© IBM UPWard 2016
79

80. T-Shaped “Future Ready” Talent
2/7/2024
© IBM UPWard 2016
80

81. Service science transdisciplinary framework
81
SYSTEMS
DISCIPLINES
transportation
& supply chain
water &
waste
food &
products
energy &
electricity
ICT &
cloud
building &
construction
retail &
hospitality
banking &
finance
healthcare
& family
education
& work
city
secure
state
scale nation laws
behavioral sciences
e.g., marketing
management science
e.g., operations
political sciences
e.g., public policy
learning sciences
e.g., game theory & strategy
cognitive sciences
e.g., psychology
system sciences
e.g., industrial engineering
information sciences
e.g., computer science
organization sciences
e.g., knowledge management
social sciences
e.g., econ & law
decision sciences
e.g., stats & design
run professions
e.g., knowledge worker
transform professions
e.g., consultant
innovate professions
e.g., entrepreneurs
change
value
technology
information
organizations
transform
(copy)
systems that govern
stakeholders
resources
customer
provider
authority
competitors
people
Innovate
(invent)
history (data
analytics)
run
future
(roadmap)
systems that focus on flows of things systems that support people's activities
Observing the stakeholders (As-Is)
Change Potential: Thinking (Has-Been & Might-Become)
Observing their Resources & Access (As-Is)
Value Realization: Doing (To-Be)
Entities
Interactions
Change
(Outcomes)
Value
(Identity)

82. Some paths to becoming 64x smarter:
Improving learning and performance
• 2x from Learning sciences (methods)
• Better models of concepts
• Better models of learners
• 2x from Learning technology (tools)
• Guided learning paths
• Elimination (?) of “thrashing”
• 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
• STEM-2D in K-12 (SSME+DAPP Design of Smart Service Systems)
• 2x from Cognitive systems (performance support)
• Technology & Infrastructure Interactions
• Organizations & Others Interactions

83. 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 83
AI Tools
in coming
decades…
2/7/2024

84. 2/7/2024
The International Society of Service Innovation Professionals
(ISSIP.org)
84

85. 85
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!)

86. 86
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!)

87. Bad Actors
Stuff

88. What expertise does
a service scientist require?
What degrees can
a service scientist earn?
Ultimately, what tool will
a service scientist most need?
Ultimately, what purpose should
a service scientist focus on?
How to invest wisely?
Year Delighted when… … and many people to thank when…
2024 IESS in Brno, Cech Republic
2023 Generative AI , Humanoid Robots, nd AI Digital Twins of Service
System Entities
2022 Exploring ServCollab and ISSIP collaborations. NAE Event on SSME in AI
Era and T-shaped Skills mentioned in Nick Donofrio Autobiography
2021 Christopher Lovelock Career Contributions to Service Discipline Award
IBMer Utpal Mangla, Elected to 2022 ISSIP VP/2023 President role
2020 Linux Foundation AI & Data TAC Chair Elected – open-source trusted AI
2019 Handbook of Service Science, Volume 2
2018 IBMer Rama Akkiraju, President of ISSIP
2017 Daniel Berg Award for Technology and Service Systems Award (IAITQM)
2016 NSF invests $13M in smart, human-centered Service Systems
2015 IBMer Jeff Welser, President of ISSIP
2014 IBM hosted Frontiers in Service Conference in San Jose, CA
2013 Vargo & Lusch S-D Logic Award, E. Gummesson Award (Naples Forum)
PICMET Fellow for Advancing Service Science
2012 International Society of Service Innovation Professionals established
2011 IBM Centennial Icon-of-Progress – including SSME and Smarter Planet
2010 Handbook of Service Science, Volume 1
2009 Robin Qiu launches INFORMS Journal of Service Science
2008 Cambridge Report – “Succeeding Through Service Innovation”
HICSS starts a service scince mini-track Paul Maglio/Furen Lin
2007 SSME in USA America COMPETES Act Congressional Legislation
IBM hosted Frontiers in Service Conference in San Francisco, CA
2006 IBM Research Awards for CBM, Data Analytics, Solution, etc. tools
2005 Attended fist Frontiers in Service – ”Big tent” getting bigger
2004 China, Japan, Finland, Germany, etc. Launch knowledge-intensive
service initiatives
2003 ”Big Tent” Service Conference at IBM Almaden, SSME Faculty Awards
2002 IBM established Almaden Service Research (ASR) group

89. Let’s level set – how many of you know about…
Ethan Mollick (UPenn Wharton) Don Norman (UC San Diego)
Scott Pelley (CBS, 60 Minutes)
Tristan Harris and Aza Raskin
(Center for Humane Technology) Generative AI Tools
To Output:
Text/Writing
Images
Code/Programming
Videos
Audio
Music
Game Worlds
Digital Twin
Other?
2/7/2024 Jim Spohrer (ISSIP.org) 89

91. 2/7/2024 91
1955 1975 1995 2015 2035 2055
Better Building Blocks

93. Domain of Science - The Map of Quantum Computing - Quantum Computing Explained
https://youtu.be/-UlxHPIEVqA

95. Week 43
NHH: FRONT LINES ON ADOPTION OF
DIGITAL AND AI-BASED SERVICES

96. 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)
2/7/2024 Jim Spohrer 96

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

98. 1960 1980 2000 2020 2040 2060 2080
Time

99. 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

100. 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 of Computation (Diagonals)

101. 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 of Computation (Diagonals)
Note: Adjust Kilo and Mega scales slightly to fit data better (early days – more cost – learning curve).

102. 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
GDP/Employee
Trend
Estimating Knowledge Worker Productivity
Based on USA
Historical Data
Year Value
1960 $10K
1980 $33K
2000 $78K
2020. $151K
2023 $169K
Cost of computation goes down by 1000x every 20 years (left to right diagonals), driving knowledge worker productivity up.

103. We get the future we invest in:
AI tools to experiment with today
• #1 Magic Eraser
• #2 Craiyon
• #3 Rytr And GPT-3, ChatGPT, GPT-4, Bing
• #4 Thing Translator
• #5 Autodraw
• #6 Fontjoy
• #7 Talk to Book
• #8 This Person Does Not Exist
• #9 Namelix
• #10 Let's Enhance
Thanks to @TessaRDavis
for compiling this list:
“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 103
Try at least two
from the list
as soon as possible
What do you think?
, DALL-E and Stable Diffusion
Every person in a role in an organization is a service provider.
2/7/2024

104. 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

105. 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)

106. Who I am: Take 2
The Three Ages of Man (Giorgione)
Thanks to Alan Hartman for kind inspiration (slides) (recording)
Service is an actor applying resources (e.g., knowledge) to benefit another
Service system entities are responsible actors that give and get service
(e.g., people, businesses, universities, nations, etc.)
Service science studies service systems as an evolving ecology
of responsible actors that interact and change.
Service innovations improve win-win interaction and change
in business and society
Service systems are dynamic configurations of four types of resources
2/7/2024 Jim Spohrer (ISSIP.org) 106
Environmental and ecological sciences
ServCollab

107. 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)

108. 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…
2/7/2024 Jim Spohrer 108

109. Narrow AI
Emerging
Broad AI
Disruptive and
Pervasive
General AI
Revolutionary
▼ We are here (2023)
2050 and beyond 109
IBM Research AI © 2018 IBM Corporation
The evolution of AI
Borrowed from David Cox, IBM-MIT Lead
▼ We were here (2018)
▼ Alan D Thompson
AGI prediction (2025)

110. Predict the Timeline: GDP/Employee
National Academy - Service Systems and AI 110
(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

111. 10 million minutes of experience
2/7/2024 Understanding Cognitive Systems 111

112. 2 million minutes of experience
2/7/2024 Understanding Cognitive Systems 112

113. Types: Progression of Models : Verified, Trusted, Wise
Models = instruction_set of future: Better building blocks
2/7/2024 Understanding Cognitive Systems 113
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

114. Resilience:
Rapidly Rebuilding From Scratch
• Dartnell L (2012) The Knowledge: How to
Rebuild Civilization in the Aftermath of a
Cataclysm. Westminster London: Penguin
Books.
2/7/2024 Jim Spohrer (ISSIP) 114
Part 3: “Solving All Problems”

115. 2/7/2024 Jim Spohrer (2015) 115
I have…
Have you noticed how the building blocks just
keep getting better?

116. Learning to program:
My first program
2/7/2024 Jim Spohrer (2015) 116
Early Computer Science Class:
Watson Center at Columbia 1945
Jim Spohrer’s
First Program 1972

117. “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

118. 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.
2/7/2024 Jim Spohrer (2017) 118

119. 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.
2/7/2024 Jim Spohrer (2017) 119

120. 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."
2/7/2024 Jim Spohrer (2017) 120

121. Part 3: “Solving All Problems”
2/7/2024 (c) IBM MAP COG .| 121

122. Backup Slides

123. Backup Slides
Microsoft Bing Images:
October 3, 2023
Prompt: Please create a funny image
of "Forrest Gump" in Silicon Valley,
running up a map of the Bay Area
and waving at some iconic companies
and people.

124. Hardware < Software < Data < Experience < Transformation
2/7/2024 Understanding Cognitive Systems 124
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

125. Intelligence Augmentation (IA) =
Socio-Technical Extension Factor on Capabilities
• Engelbart (1962)
• Spohrer & Engelbart (2002)
2/7/2024 Jim Spohrer (ISSIP) 125
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.

126. 2/7/2024 Jim Spohrer (ISSIP.org) 126
0 25 50 100 125 150
Automobile
75
Years
50
100
Telephone
Electricity
Radio
Television
VCR
PC
Cellular
%
Adoption
Capability Augmentation and Adoption Rate Increases

127. Courses
• 2015
• “How to build a cognitive system for Q&A task.”
• 9 months to 40% question answering accuracy
• 1-2 years for 90% accuracy, which questions to reject
• 2025
• “How to use a cognitive system to be a better
professional X.”
• Tools to build a student level Q&A from textbook in 1
week
• 2035
• “How to use your cognitive mediator to build a
startup.”
• Tools to build faculty level Q&A for textbook in one day
• Cognitive mediator knows a person better than they
know themselves
• 2055
• “How to manage your workforce of digital workers.”
• Most people have 100 digital workers.
2/7/2024 127
Take free online cognitive classes today at cognitiveclass.ai

128. Estimating Knowledge Worker Productivity
• Estimation Framework (Time and Cost)
• Draw seven vertical lines, label them with year from 1960 to 2080
• Draw five horizontal lines, label them with dollars from $1 to $Trillion
• Estimating Cost of Computation
• Add horizontal lines – that is Moore’s Law – cost of computation as a function of
time from Kiloscale (103) to Ronnascale (1027)
• Estimating Human-Scale Comparison
• Make Exascale (1018) thicker – estimated computing power of 1 person’s brain
• Make Ronnascale (1027) thicker – estimated computing power of a billion brains
• Estimating Knowledge Worker Productivity
• Add GPD/Employee in USA – that is an estimate of knowledge worker productivity

129. 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
Estimating Human-scale Comparison
Human-scale
Brains Compute
One Exa- (1018)
Billion Ronna- (1027)

130. Estimating Knowledge Worker Productivity

131. 2/7/2024 Jim Spohrer (ISSIP.org) 131
(Chorus)
AI, AI, enhancing the way,
Personalization brightens each day.
With tailored recommendations, it's clear,
SIR members' interests, AI holds dear.
Oh, SIR, SIR, hear this tune so true
ChatGPT Prompt: Please transform
the essay “AI for SIR members” into a song
to the tune of "Daisy, Daisy give me
your answer do”
DALL-E Prompt: Generate a painting
of the essence of technology and camaraderie
with a vibrant and engaging image of retired men
singing together. Evoke a sense of excitement and
showcase the power of AI in enhancing the lives of
SIR members.

132. Adjustment Period:
“Drinking from a firehose”
• Everyday, new AI announcements (globally)
• Hype at all time high
• Progress at all time high
• Adjustment period will last for a few decades
• Stay focused on a problem you are trying to solve
• … What problem would you be working to solve…
• if you had 100 digital workers working for you every minute of the day (24x7)?
• … How much decarbonized/carbonized energy are they consuming?
• … How much harm are bad actors causing using AI tools, etc.?
• … How well are the populations of whole nations doing on AI upskilling?
• … How to help responsible actors learning to invest better in win-win interactions
and change, to get the future that they want?
2/7/2024 Jim Spohrer (ISSIP.org) 132
DALL-E 2 Prompt:
A crowd of people struggling to drink
from a steampunk robot firehouse
gushing knowledge
in the style of Norman Rockwell

133. We get the future we invest in:
AI tools to experiment with today
• #1 Magic Eraser
• #2 Craiyon
• #3 Rytr And GPT-3, ChatGPT, GPT-4, Bing
• #4 Thing Translator
• #5 Autodraw
• #6 Fontjoy
• #7 Talk to Book
• #8 This Person Does Not Exist
• #9 Namelix
• #10 Let's Enhance
Thanks to @TessaRDavis
for compiling this list:
“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 133
Try at least two
from the list
as soon as possible
What do you think?
, DALL-E and Stable Diffusion
Every person in a role in an organization is a service provider.
2/7/2024

134. June 12, 2022 – The Economist
Magazine Cover
March of the machines
A SPECIAL ISSUE ON ARTIFICIAL INTELLIGENCE
June 21, 2022 – COSMOPOLITAN
Magazine Cover – The A.I. Issue
Meet the World’s First
Artificially Intelligent Magazine Cover
And it only took 20 seconds to make
Historic Examples of AI’s Foundational Models Becoming Useful

135. https://service-science.info/archives/6377

136. DALL-E Prompt:
Create an image that illustrates
a person upskilling with AI,
showing their determination
and resilience in the face of
uncertainty and change.
The image should convey the
idea that upskilling with AI is a
way for individuals to stay
ahead in the job market
and be prepared for the future
of work. The person in the
image should be depicted
as confident and focused,
surrounded by technology and
tools that symbolize their
journey towards upskilling in AI.
The overall feel of the image
should be modern, sleek,
and inspiring.
Upskilling with AI: Staying
Resilient in Uncertain
Times

137. Upskilling with AI: Staying
Resilient in Uncertain Times
DALL-E Prompt:
Create a magazine cover image
that captures the theme of
"Upskilling with AI: Staying Resilient
in Uncertain Times". The image
should show a person
who is determined and optimistic,
despite the challenges of the
current job market and economic
uncertainty. They should be
depicted as actively engaged in
learning and improving their
AI skills, surrounded by cutting-edge
technology.

138. Philippe Deridder
AI Tools for Innovation
• URL -
https://www.linkedin.com/p
osts/philippederidder_innov
ation-design-ux-activity-
7044345913770700800-
6_V7
2/7/2024 Jim Spohrer (ISSIP.org) 138

139. Part 1: Solving AI
• Technical challenges and social adjustment period
2/7/2024 Jim Spohrer (ISSIP.org) 139

140. Questions
• 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?
2/7/2024 Jim Spohrer (2017) 140

141. Timeline: Short History
2/7/2024
Jim Spohrer (2017)
141
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.

142. Rapid Progress
• History and Future
2/7/2024 Jim Spohrer (ISSIP.org) 142

143. Timeline: Every 20 years,
compute costs are down by 1000x
• Cost of Digital Workers
• Moore’s Law can be thought of as
lowering costs by a factor of a…
• Thousand times lower
in 20 years
• Million times lower
in 40 years
• Billion times lower
in 60 years
• Smarter Tools (Terascale)
• Terascale (2017) = $3K
• Terascale (2020) = ~$1K
• Narrow Worker (Petascale)
• Recognition (Fast)
• Petascale (2040) = ~$1K
• Broad Worker (Exascale)
• Reasoning (Slow)
• Exascale (2060) = ~$1K
143
2/7/2024 Jim Spohrer (2017)
2080
2040
2000
1960
$1K
$1M
$1B
$1T
2060
2020
1980
+/- 10 years
$1
Person Average
Annual Salary
(Living Income)
Super Computer
Cost
Mainframe Cost
Smartphone Cost
T
P
E
T P E
AI Progress on Open Leaderboards
Benchmark Roadmap to solve AI/IA

144. Predict the Timeline: GDP/Employee
National Academy - Service Systems and AI 144
(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

145. 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
2/7/2024 Jim Spohrer (2017) 145
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

146. 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
2/7/2024 Jim Spohrer (2017) 146
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

147. From leaderboards
to profession exams
2/7/2024 (c) IBM MAP COG .| 147

148. Leader Boards:
Professional
Benchmarking
2/7/2024 Jim Spohrer (ISSIP.org) 148

149. Professional
Benchmarking
2/7/2024 Jim Spohrer (ISSIP.org) 149

150. Who is winning
2/7/2024 Jim Spohrer (2017) 150
https://www.technologyreview.com/s/608112/who-is-winning-the-ai-race/

151. GPT-4:
Needs more
planning
capability
2/7/2024 Jim Spohrer (ISSIP.org) 151

152. OpenAI GPT:
Enterprise
Customers
2/7/2024 Jim Spohrer (ISSIP.org) 152
Alan D. Thompson
Lifearchitect.ai

153. Open Source AI:
Not Wise?
Or Super Wise?
2/7/2024 Jim Spohrer (ISSIP.org) 153
Some say: When you have nothing,
And you want attention – open source.
However, as soon as you have something,
And you are competitive, you put up
A “CLOSED” sign – as quick as you can.
Nonzero sum trailer, becomes zero-sum leader.

154. LLaMa &
Alpaca
• Open Source
• Training Cost
Declining
2/7/2024 Jim Spohrer (ISSIP.org) 154

155. Who I track to learn about new AI tools to use
• Alan D. Thompson
• https://lifearchitect.ai/how-do-
i-talk-to-gpt/
• https://youtu.be/D3tTsoX02d8
2/7/2024 Jim Spohrer (ISSIP.org) 155

156. 2/7/2024 Jim Spohrer (ISSIP.org) 156
Jim Spohrer (2022):
3-4x the time seems
more realistic to me,
so perhaps by 2050-2060.
AI advances and adoption
are both very hard.

157. Robots by Country
• Industrial robots per 10,000 people by country
2/7/2024 Jim Spohrer (2017) 157
34

158. Sweden
2/7/2024 (c) IBM MAP COG .| 158

159. Economic Growth Rates 2035: AI Projected Impact
2/7/2024 Jim Spohrer (2017) 159

160. Science gathers
knowledge
>>>
Society gathers
wisdom
2/7/2024 Jim Spohrer (ISSIP.org) 160

161. 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
2/7/2024 Jim Spohrer (2017) 161

162. AI Risks
• Job Loss
• Shorter term bigger risk
= de-skilling
• Super-intelligence
• Shorter term bigger risk
= bad actors
2/7/2024 Jim Spohrer (2017) 162

163. 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.)
2/7/2024 Jim Spohrer (2017) 163

164. Emergence
• Capabilities in larger
models, not in
smaller models
2/7/2024 Jim Spohrer (ISSIP.org) 164

165. Theory of Mind
• Theory of Mind: When an
entity has an accurate
idea of what’s going on in
other entities’ minds,
including when the other
entity is right and wrong.
• Sutskever (OpenAI Chief
Scientist): ”We are
starting to reach a point,
where the language of
psychology is starting to
be appropriate to
understand the behavior
of these neural networks.”
2/7/2024 Jim Spohrer (ISSIP.org) 165

166. AGI:
Embodied
• Stages
• OpenAI >
Anthropic
• Getting harder to
keep up with
improvements
• Outlier tests get
harder and
harder
2/7/2024 Jim Spohrer (ISSIP.org) 166

167. AGI
Thinking
Acting
• 34 months away?
• 2026?
• Human-level across
all disciplines
2/7/2024 Jim Spohrer (ISSIP.org) 167

168. Part 2: Solving IA
• Rapidly advancing technology and social adjustment (regulations)
period
2/7/2024 Jim Spohrer (ISSIP.org) 168

169. Smartphones pass entrance exams? When?
2/7/2024 IBM 2017, Cognitive Opentech Group 169
… when will
your smartphone
be able to take and
pass any online
course? And then
be your coach, so
you can pass too? OpenAI Answer:
2023
My Question:
2017

170. Types: Progression of Models : Trusted, Verified, Wise
Models = instruction_set of future: Better building blocks
2/7/2024 Understanding Cognitive Systems 170
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

171. 2/7/2024 Jim Spohrer (ISSIP.org) 171

172. 2/7/2024
© IBM 2015, IBM Upward University Programs Worldwide
accelerating regional development
172
Cognitive Mediators
for all people in all roles

173. Occupations = Many Tasks
2/7/2024 Jim Spohrer (2015) 173

174. Watson Discovery Advisor
2/7/2024 Jim Spohrer (2015) 174
Simonite, T. 2014. Software Mines Science Papers to Make New Discoveries. MIT. November 25, 2014.
URL: http://m.technologyreview.com/news/520461/software-mines-science-papers-to-make-new-discoveries/

175. 10 million minutes of experience
2/7/2024 Understanding Cognitive Systems 175

176. 2 million minutes of experience
2/7/2024 Understanding Cognitive Systems 176

177. Hardware < Software < Data < Experience < Transformation
2/7/2024 Understanding Cognitive Systems 177
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

178. Intelligence Augmentation (IA) =
Socio-Technical Extension Factor on Capabilities
• Engelbart (1962)
• Spohrer & Engelbart (2002)
2/7/2024 Jim Spohrer (ISSIP) 178
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.

179. 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
2/7/2024 Jim Spohrer (ISSIP) 179
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)

180. 2/7/2024 Jim Spohrer (ISSIP.org) 180
0 25 50 100 125 150
Automobile
75
Years
50
100
Telephone
Electricity
Radio
Television
VCR
PC
Cellular
%
Adoption
Capability Augmentation and Adoption Rate Increases

181. Courses
• 2015
• “How to build a cognitive system for Q&A task.”
• 9 months to 40% question answering accuracy
• 1-2 years for 90% accuracy, which questions to reject
• 2025
• “How to use a cognitive system to be a better
professional X.”
• Tools to build a student level Q&A from textbook in 1
week
• 2035
• “How to use your cognitive mediator to build a
startup.”
• Tools to build faculty level Q&A for textbook in one day
• Cognitive mediator knows a person better than they
know themselves
• 2055
• “How to manage your workforce of digital workers.”
• Most people have 100 digital workers.
2/7/2024 181
Take free online cognitive classes today at cognitiveclass.ai

182. 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 182
AI Tools
in coming
decades…
2/7/2024

183. TacitPath.Com: Entity Coordination Via Shared
Information – John Wolpert
2/7/2024 Jim Spohrer (ISSIP.org) 183

185. Part 3: “Solving All Problems”
2/7/2024 (c) IBM MAP COG .| 185

186. 2/7/2024 Jim Spohrer (2015) 186
I have…
Have you noticed how the building blocks just
keep getting better?

187. Learning to program:
My first program
2/7/2024 Jim Spohrer (2015) 187
Early Computer Science Class:
Watson Center at Columbia 1945
Jim Spohrer’s
First Program 1972

188. 2/7/2024 188
1955 1975 1995 2015 2035 2055
Better Building Blocks

189. “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

190. 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.
2/7/2024 Jim Spohrer (2017) 190

191. 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.
2/7/2024 Jim Spohrer (2017) 191

192. 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."
2/7/2024 Jim Spohrer (2017) 192

193. 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

194. 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)

195. Artificial Intelligence (AI) has come a long way in almost seven decades…
From David Michaelis, I4J Forum

196. … but we still
have a long
way to go.
https://blog.irvingwb.com/blog/
January 26, 2023
Technical challenges no longer the hardest part, the AI to IA adjustment period is about responsible actors upskilling.

197. Overlap
Acknowledgement: E. Noei, S. Brisson, Y. Liu
Via Kelly Lyons, NAE Talk Oct 2022
2010
2019
197
Service science has come a long way in two decades…
2004-2011

198. … but we still
have a long
way to go.
https://blog.irvingwb.com/blog/
December 1, 2022

199. Trust: Two Communities
2/7/2024 Jim Spohrer (2018) 199
Service
Science
OpenTech
AI
Trust:
Value Co-Creation,
Transdisciplinary
Trust:
Ethical, Safe, Explainable,
Open Communities
Special Issue
AI Magazine?
Handbook of
OpenTech AI?

200. Today’s Books
Service is the application of resources (e.g., knowledge) for the benefit of another*
* another includes your future self and future generations as well.
The two greatest challenges of the 21st century are simultaneously
upskilling entire nations with AI (knowledge infrastructure, digital transformation)
while decarbonizing entire nations (energy infrastructure, physical transformation).
And accomplishing both with globally sustainable as-a-service models - servitization.

201. 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

202. 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

203. 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

204. 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

205. Humanity-Centered Harmonization of AI for Service

206. 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.
2/7/2024 National Academy - Service Systems and AI 206

207. 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 207
6 T-shape Skills
Knowledge Areas
To be eXtended
By AI tools:
1. Disciplines
2. Systems
3. Cultures
4. Technologies
5. Practices
6. Mindsets
2/7/2024

208. How, What, and Why?
Inspiring AI upskilling (IA)
• 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 208

209. We get the future we invest in:
AI tools to experiment with today
• #1 Magic Eraser
• #2 Craiyon
• #3 Rytr And GPT-3, ChatGPT, GPT-4, Bing
• #4 Thing Translator
• #5 Autodraw
• #6 Fontjoy
• #7 Talk to Book
• #8 This Person Does Not Exist
• #9 Namelix
• #10 Let's Enhance
Thanks to @TessaRDavis
for compiling this list:
“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 209
Try at least two
from the list
as soon as possible
What do you think?
, DALL-E and Stable Diffusion
Every person in a role in an organization is a service provider.
2/7/2024

210. 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 210
Read enough of IfM and IBM (2008)
to understand what a “Service Innovation
Roadmap (SIR)” is – and who should be
creating them.
2/7/2024

211. Learning to invest
• Run = Routine Activities
• Transform = Copy Activities
• Innovate =
Invent and Apply Activities
2/7/2024 Jim Spohrer (ISSIP.org) 211
Innovate
Invest in each
type of change

212. 212
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) Innovate
Invest in each
type of change
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

213. Concluding Remarks: Two Books
2/7/2024 Jim Spohrer (ISSIP.org) 213

214. Better Models (Spohrer, Maglio, Vargo, Warg 2022)
• Increasing complex, interconnected world
• All models are wrong, some are useful
• Better models are needed of
• the world – both physical, social, virtual (science)
• people and win-win interactions (logics)
• organizations and win-win change (architecture)
• technologies (AI)
• Better models for better investing
• “We get the future we invest in, so responsible
actors must learn to invest wisely and
systematically in improved win-win interaction
and change.”
2/7/2024 Jim Spohrer (ISSIP.org) 214

215. 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)

216. From Human-Centered to Humanity-Centered Design (Norman 2023)
• Human-Centered Design
1. Solve the core, root issues, not just the
problem as presented (which is often the
symptom, not the cause).
2. Focus on the people.
3. Take a systems point of view, realizing
that most complications result from the
interdependencies of the multiple parts.
4. Continually test and refine the proposed
designs to ensure they truly meet the
concerns of the people for whom they
are intended.
2/7/2024 Jim Spohrer (ISSIP.org) 216
• Humanity-Centered Design
1. Solve the core, root issues, not just the
problem as presented (which is often the
symptom, not the cause).
2. Focus on the entire ecosystem of people, all
living things, and the physical environment.
3. Take a long-term, systems point of view,
realizing that most complications result from
the interdependencies of the multiple parts
and that many of the most damaging impacts
on society and the ecosystem reveal
themselves only years or even decades later.
4. Continually test and refine the proposed
designs to ensure they truly meet the concerns
of the people and ecosystem for whom they
are intended.
5. Design with the community and as much as
possible support designs by the community.
Professional designers should serve as
enablers, facilitators, and resources, aiding
community members to meet their concerns.

217. Discussion
• Are you positive or negative about AI?
• If positive, are you using any specific AI tools today?
• See list of AI tools to try on a previous slide
• How are you investing in upskilling with AI?
• If negative, do you have a specific concern (“ditch to avoid”) – for example…?
• AI will take away my job
• AI will be used primarily by “bad actors” for mischief
• Or used by social media platforms to generate more clicks/attention thru angry
reactions
• AI will try to take over people and planet
• AI will deskill and weaken people over time
• … or other concerns about AI?
• Do you believe responsible actors (e.g., people, businesses,
universities, governments, etc.) are learning to to invest
systematically and wisely in getting the future we want? If not, why
not – what is needed?
• Join ISSIP.org (free for individuals) if you would like to continue the
conversation!
National Academy - Service Systems and AI 217
Read enough of pages 45-54 of Spohrer, Maglio, Vargo, Warg (2022) to formulate an
opinion on the topic of “investing wisely to get the future service systems we want.”
2/7/2024

218. Be Prepared
• Understand open AI code + data +
models + stacks + communities
• Leaderboards
• Ethical conduct
• Learn 3 R’s of IBM’s Cognitive
Opentech Group (COG)
• Read arXiv
• Redo with Github
• Report with Jupyter notebooks on DSX
and/or leaderboards
• Improve your team’s skills of rapidly
rebuilding from scratch
• Build your open code eminence
• Understand open innovation
• Communities + Leaderboards
2/7/2024 Jim Spohrer (2017) 218
1972 used
Punch cards
2016 used
IBM Watson
Open APIs to win…
2022
OpenAI DALL-E 2
and ChatGPT
2023
GPT-4

219. Resilience:
Rapidly Rebuilding From Scratch
• Dartnell L (2012) The Knowledge: How to
Rebuild Civilization in the Aftermath of a
Cataclysm. Westminster London: Penguin
Books.
2/7/2024 Jim Spohrer (2017) 219
What if the ”bad actors” get the upper hand?

220. The best tool: Our brains and models of the
resources in the world & responsible actors
https://www.pdfdrive.com/the-discipline-of-organizing-e34689259.html

221. Why I am optimistic

223. Who I am: Take 2
The Three Ages of Man (Giorgione)
Thanks to Alan Hartman for kind inspiration (slides) (recording)
Service is an actor applying resources (e.g., knowledge) to benefit another
Service system entities are responsible actors that give and get service
(e.g., people, businesses, universities, nations, etc.)
Service science studies service systems as an evolving ecology
of responsible actors that interact and change.
Service innovations improve win-win interaction and change
in business and society
Service systems are dynamic configurations of four types of resources

224. 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

225. 2/7/2024
The International Society of Service Innovation Professionals
(ISSIP.org)
225

226. IA Progression – Tool, Assistant, Collaborator, Coach, Mediator
2/7/2024 Jim Spohrer (ISSIP) 226
Rouse & Spohrer (2018)
Siddike, Spohrer, Demirkan, Kodha (2018)
Araya (2018)
Spohrer& Siddike (2018)

227. “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

228. 2/7/2024 228
1955 1975 1995 2015 2035 2055
Better Building Blocks

229. Additional Resources
• Arthur WB (2019) Foundations of Complexity Economics. Nature Review Physics.
• Dietrich BL, Plachy EC, Norton MF (2014) Analytics Across the Enterprise.
• Donofrio N, DeMarco M (2022) If Nothing Changes, Nothing Changes: The Nick Donofrio.
• Fleming M (2022) Breakthrough: The Growth Revolution (in an Era of Artificial Intelligence and Worker Engagement).
• IfM and IBM (2008) Succeeding through service innovation: A service perspective for education, research, business and government.
• Larson RC (2022) Model Thinking for Everyday Life Working Wonders with a Blank Sheet of Paper. (Coming Soon).
• Lebovitz S, Lifshitz-Assaf H, Levina N (2022) To Engage or Not to Engage with AI for Critical Judgments: How Professionals Deal with Opacity When Using AI for Medical Diagnosis. Organization Science.
• Madhavan G, Poste G, Rouse W (2020) Complex Unifiable System. Editors' Note: Systemic Vistas. Winter 2020. The Bridge.
• Maglio PP, Kieliszewki CA, Spohrer JC (2010) Handbook of Service Science
• Maglio PP, Kieliszewki CA, Spohrer JC, Lyons K, Patrício L, Sawatani Y (2019) Handbook of Service Science, Vol II
• McDermid JA (2022) Safe, Ethical & Sustainable: A Mantra for All Seasons?
• Munn L (2022) The uselessness of AI ethics.
• Norman D (2023) Design for a Better World: Meaningful, Sustainable, Humanity Centered
• Rouse WB (2018) Life with a cognitive assistant. (2022) Emily 2.0..
• Rouse WB, Spohrer JC (2018) Automating versus augmenting intelligence. Journal of Enterprise Transformation.
• Schneiderman (2022) Human-Centered AI.
• Spohrer J (2017) Imagination Challenge: Quantify and graph cost of digital workers and GDP per employee USA from 1960-2080.
• Spohrer J, Maglio, PP (2009) Service Science: Toward a Smarter Planet. In Service Engineering.
• Spohrer J, Maglio PP, Vargo SL, Warg M (2022) Service in the AI Era: Science, Logic, and Architecture Perspectives.
• US 110th Congress (2007) SEC. 1005. STUDY OF SERVICE SCIENCE.
• Vargo SL, Lusch RF (2016) Institutions and Axioms: An Extension and Update of Service-Dominant Logic. JAMS.
• Wakefield J (2022) Why you may have a thinking digital twin within a decade. BBC News Online.
• West S, Meierhofer J, Mangla U (2022) Smart Services Summit: Smart Services Supporting the New Normal.
• 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.
• Wladalsky-Berger I (2016) The Continuing Evolution of Service Science. (2019) The Increasing Demand for Hybrid, “T-Shaped” Workers . (2021) The Supply Chain Economy - A New Categorization of the US Economy (2022) A New
Measurement Framework for the Digital Economy. (2022) Foundation Models: AI’s Exciting New Frontier.
Service Systems Engineering in the Human-Centered AI Era 229

230. 2/7/2024 Jim Spohrer (ISSIP.org) 230
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

231. Service Science: Conceptual Framework
2/7/2024 (c) IBM MAP COG .| 231
Service Science

232. (c) IBM MAP COG .| 232
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)

233. 233
Time
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

234. Early Motivations (Growth 2)
2/7/2024 (c) 2014 IBM UP (University Programs) 234
Gerstner decides
to grow service

235. Early Motivations (Aspiration 2)
2/7/2024 (c) 2014 IBM UP (University Programs) 235

236. Principle 1: Resources
2/7/2024 (c) 2014 IBM UP (University Programs) 236

237. Principle 2: Value Propositions
2/7/2024 (c) 2014 IBM UP (University Programs) 237

238. Principle 3: Access Rights
2/7/2024 (c) 2014 IBM UP (University Programs) 238

239. Principle 4: Outcomes
2/7/2024 (c) 2014 IBM UP (University Programs) 239

240. Principle 6: Entities
2/7/2024 (c) 2014 IBM UP (University Programs) 240

241. 2/7/2024 © IBM 2015, IBM Upward University Programs
Worldwide accelerating regional development
241
Explain phenomena
and build better
tools and systems

242. 242
A Game of Life: Essentials
• Game = board with squares & rules
– Infrastructure both Environmental and Technological
• PS (Physical Systems - Environment)
– Natural Endowment (hidden & observable information)
• PSS (Physical Symbol Systems – Environment & Technology)
– Biological PSS (observable information – DNA, RNA, proteins, etc.)
– Technological PSS (observable information – states of system, bits, etc.)
• Life = multiple generations of entities
– Entities = SSE (Service System Entities)
• Individuals with Competencies & Life-Spans
– Competencies (vary with age)
– Life-Spans (vary with stage)
• Institutions with Roles & Rules
– Roles (Competency-Levels and Pay-Levels)
– Rules (Compliance-Levels and Tax-Levels) Physical
Not-Physical
Rights No-Rights
2. Technology/
Environmental
Infrastructure
4. Shared
Information
1. People/
Individuals
3. Organizations/
Institutions
1. Dynamically configure resources (4 I’s)

243. 243
Life = Multiple Generations of Entities (200 years = 10 generations x 20 years)
Pedagogy: Ten Social-Technological-Economic-Environmental-Political (STEEP) Stages
Thought Experiment: Binary-Board-Space (Rule: Toggles Each Generation)
1. Hunter-Gatherer Knowledge-Value Economy 1
- 2K population (20 people/sq mile * 100 sq miles)
2. Transition Hunter-Gatherer Knowledge-Value Economy 2
- 4K population (40 people/sq mile * 100 sq miles)
3. Agricultural Knowledge-Value Economy 1
- 8K population (80 people/sq mile * 100 sq miles)
4. Transition Agricultural Knowledge-Value Economy 2
- 16K population (160 people/sq mile * 100 sq miles)
5. Manufacturing Knowledge-Value Economy 1
- 32K population (320 people/sq mile * 100 sq miles)
6. Transition Manufacturing Knowledge-Value Economy 2
- 64K population (640 people/sq mile * 100 sq miles)
7. Service-Information Knowledge-Value Economy 1
- 128K population (1,280 people/sq mile * 100 sq miles)
8. Transition Service-Information Knowledge-Value Economy 2
- 256K population (2,560 people/sq mile * 100 sq miles)
9. Sustainable-Innovation Knowledge-Value Economy 1
- 512K population (5,120 people/sq mile * 100 sq miles)
10.Transition Sustainable-Innovation Knowledge-Value Economy 2
- 1024K population (10,240 people/sq mile * 100 sq miles)
11.And beyond!
10 miles
In Use
Recycle
Rule:
Toggles
Each
Generation

244. 244
Game = Board with Squares & Rules
Example: Possible STEEP Stages 9 & 10 (infrastructure, sustainable-innovation cities)
• Imagine nested holistic product-service-systems entities…
– 10 Continents/planet
– 10 Nations/continent
– 10 States/nation
– 10 Cities/state
– 4 Sectors/city (interconnect to others)
– 11 Systems/sector
• Rules: Board-space toggles each generation
– 20 years/generation
– New infrastructure/generation
• World: Further Pedagogical Purposes
– “World Simulator” benchmarking
– Search to accelerate learning
• 10,000 city experiments/generation
• Low skill/raw materials > Hi-talent/tech
– Each generation new outcomes
• Talents (skills & jobs)
• Technologies (recycle & rebuild)
• Investments (script & performance)
Occupied
(In Use)
Recycling
(De-construction &
Re-construction)
water
food/products
energy
ICT
R&H/M&E/C&S
finance
health
education
governance
transportation
buildings/family
Sector 1
city
interconnect
11 Systems
Sector 2
state
interconnect
Sector 3
nation
interconnect
Sector 4
continent
interconnect
Toggle
each
generation
–
20
year
cycle

245. 245
Entities = Life-Cycle Script
Example: Possible STEEP Stages 9 & 10 (individuals, multiple generations of entities)
• Children – Age 0-20
– (Local & Global) Grow, Learn, & Have Fun
• Parents – Age 20-40 (offspring 2)
– (Next Local) Reproduce, Raise Children, & Build New “City” SET Stage
• Grand-Parents – Age 40-60 (offspring 4)
– (Local) Run the “City” You Built & Connect with Family
• Great-Grand-Parents – Age 60-80 (offspring 8)
– (Global) Travel the World, Enjoy Experiences, & Share Ideas
• Great-Great-Grand-Parents – Age 80-100 (offspring 16)
– (Local) Return, Reconnect, and Document History & Future Plans
• Great-Great-Great-Grand-Parents – Age 100-120 (offspring 32)
– (Local & Global) Celebrate, Tell Stories, Depart & Explore Further Realms

246. 246
The Game of Life: Service Science
Framework
• The Game Board: A configuration of PS (Physical Systems), with interspersed PSS
(Physical Symbol Systems) and SSE (Service System Entities).
– The SSE are PSS are PS
– The infrastructure is PS + PSS
• The PS have hidden information (state)
• The PSS have observable information (state and read-write)
– The SSE use information to co-create value
• World model – information about the world (The Game Board)
• Self model – information about self (SSE)
• The SSE have a beginning and an end (life-cycle)
• The SSE judge quality-of-life across their life-cycle
– The game is each generation of SSE try to improve quality-of-life, by improving the capabilities
of the infrastructure (less waste, more support for SSE activities) and the capabilities of the
SSE to co-create value (an SSE activity)
– The starting game board consists of PS with a few PSS, and the goal is to see how quickly and
with how little energy and with how few types and tokens of PS, the PSS can become SSE and
reconstruct a high level infrastructure and high quality of life and continuously improve at a
sustainable pace.
• Processes of valuing are based on the above

247. 247
Thought Experiment: People
Youth (20%)
Elderly (20%)
Prisoners (5%)
Disabled (5%)
Retired (5%)
Unemployed (5%)
Workers (40%)
Workers (40%)
Public (5%)
Private (35%)
For-Profit (25%)
Publicly Traded (10%)
Privately Held (15%)
Not-For-Profit (10%)
Paid (5%)
Endowed (1%)
Donations & Grants (3%)
At-Home-Workers (1%)
Unpaid (5%)
At-Home-Workers (5%)