In the presentation, Jim Spohrer discusses the dual challenges of upskilling nations through AI and decarbonizing them, advocating for responsible investment in service innovation roadmaps. He highlights that while service providers using AI can enhance value co-creation, those who neglect AI may fall behind. Spohrer calls for a collaborative approach to navigate complex systems and ensure sustainable futures in service science and AI.

1. 2022 ASAP
Service in the AI Era:
A Service Science Perspective
Jim Spohrer
Retired Executive – IBM and Apple
UIDP Senior Fellow & Member ISSIP.org
Questions: spohrer@gmail.com
Twitter: @JimSpohrer
LinkedIn: https://www.linkedin.com/in/spohrer/
Slack: https://slack.lfai.foundation
Presentations online at: https://slideshare.net/spohrer
Thanks to Marrio Rapaccini and Nicola Saccani for the invitation
to discuss Service in the AI Era
Thursday November 10, 2022, 11:00-12:00 Italy Time
Highly recommend:
Humankind: A Hopeful History
By Dutch Historian, Rutger Bregman
<- Thanks
To Ray Fisk
For suggesting
this book, see
My summary here.
See also
ServCollab.

2. https://issip.org/awards-excellence-in-service-innovation/
ISSIP Excellence
in Service
Innovation
Awards
11/10/2022 2
Call for Nominations!
(deadline Dec. 31, 2021)

3. Today’s Talk
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.

4. 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) 4
9/2/22

5. 11/10/2022 Jim Spohrer (ISSIP.org) 5
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.

6. 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 6
6 T-shape Skills
Knowledge Areas
To be eXtended
By AI tools:
1. Disciplines
2. Systems
3. Cultures
4. Technologies
5. Practices
6. Mindsets
11/10/2022

7. AI Tools to Experiment with Today
• #1 Magic Eraser
• #2 Craiyon
• #3 Rytr And GPT-3
• #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 service providers
who do not use AI
will be replaced by
those who do.”
National Academy - Service Systems and AI 7
Try at least two
from the list
as soon as possible
What do you think?
And Stable Diffusion
Every person in a role in an organization is a service provider.
11/10/2022

8. Predict AI Timeline: GDP/Employee
National Academy - Service Systems and AI 8
(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
11/10/2022

9. 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 9
AI Tools
in coming
decades…
11/10/2022

10. 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 10
Read enough of IfM and IBM (2008)
to understand what a “Service Innovation
Roadmap (SIR)” is – and who should be
creating them.
11/10/2022

11. 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 11
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.”
11/10/2022

12. 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 12

13. 11/10/2022 Jim Spohrer (ISSIP.org) 13
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

14. Learning to invest
• Run = Routine Activities
• Transform = Copy Activities
• Innovate =
Invent and Apply Activities
11/10/2022 Jim Spohrer (ISSIP.org) 14
Innovate
Invest in each
type of change

15. 15
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

16. Why the trend towards increasingly complex systems is important
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 soci—technical system design loop concepts.
11/10/2022 National Academy - Service Systems and AI 16

17. Jim Spohrer, Board of Directors, ISSIP.org
Jim Spohrer serves on the Board of Directors of the International Society of
Service Innovation Professionals, and as a contributor to the Linux Foundation
AI and Data Foundation. He 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. After his
MIT BS in Physics, he developed speech recognition systems at Verbex (Exxon)
before receiving his Yale PhD in Computer Science/AI. In the 1990’s, he attained
Apple Computers’ Distinguished Engineer Scientist and Technologist role for
next generation learning platforms. With over ninety publications and nine
patents, he received the Christopher Loverlock 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 LF AI & Data Technical Advisory Board Chairperson and ONNX Steering
Committee Member (2020-2021), UIDP Senior Fellow for contributions to
industry-university collaborations.
17
From 2002 - 2009, Jim co-founded
IBM Almaden Service Research (ASR)
ASR mission - advance service science
and people-centered, data-intensive
service innovation
Who I am

18. 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

19. 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

20. 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)

21. ISSIP: Service Innovation and T-Shaped Adaptive Innovators Breadth
Depth
Breadth
Depth
Depth
Depth
Breadth
Breadth
Breadth
Depth
Depth
Depth
Breadth
Breadth
Breadth
Depth
Depth
Depth
Breadth
Breadth
Communications
Problem
Solving
Cultures
Systems
Disciplines
Cultures
Disciplines
Systems
Cultures
Systems
Disciplines
Cultures
Disciplines
Systems
Mindsets
Mindsets
Work
Practices
Advancing
Tech.
Work Practices
Advancing Tech.
Individual Expertise – T1, T3
Collective Expertise – T6
Augmented Expertise – T6
Role
Skills
Identity
Threatened Empowered
Service
Offerings
Service-for-Service
Exchange
Sustaining “mindsets” requires “like-minded”
Sustaining “innovation” requires “depth-diversity-inclusion”
Sustaining above requires “lifelong learning – interaction & change”
Sustaining people requires “rhythmic cycles” – breath, drink & eat, sleep, etc.
T1
T3
T6
I
We
I
We
Me
Me

23. 5/18/22, 6:57 AM
Page 1 of 2
https://media.licdn.com/embeds/native- document.html?li_theme=light
See Ricardo Martins - https://www.linkedin.com/in/ricardoalexmartins/

25. Early Service Science Work
• Revisiting SSME and T-Shaped Skills in the AI Era
• SERVICE SCIENCE DEFINED.—In this section, the term ‘‘service
science’’ means curricula, training, and research programs that
are designed to teach individuals to apply scientific, engineering,
and management disciplines that integrate elements of
computer science, operations research, industrial engineering,
business strategy, management sciences, and social and legal
sciences, in order to encourage innovation in how organizations
create value for customers and shareholders that could not be
achieved through such disciplines working in isolation.” (US 110th
Congress 2007)
• T-SHAPED SKILLS DEFINED. – T-shaped skills is a metaphor for
describing the skills of a person who combines both breadth and
depth, like the shape of the letter T - a combined generalist with
excellent interactional communication skills across business and
technology as well as a specialist in one or more areas with
contributory problem-solving skills, the area(s) of the person’s
earned “bon fides.” (see also IfM and IBM 2008).
Service Systems Engineering in the Human-Centered AI Era 25
Nick Donofrio
IBM Fellow Emeritus
NAE Member

26. Service Systems Engineering in the Human-Centered AI Era 26
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

27. Overlap
Acknowledgement: E. Noei, S. Brisson, Y. Liu
2010
2019
27
Kelly Lyons

28. Service Science: Conceptual Framework
11/10/2022 (c) IBM MAP COG .| 28
Service Science

29. (c) IBM MAP COG .| 29
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)

30. Concluding Remarks: Two Books
11/10/2022 Jim Spohrer (ISSIP.org) 30

31. 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.”
11/10/2022 Jim Spohrer (ISSIP.org) 31

32. 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.
11/10/2022 Jim Spohrer (ISSIP.org) 32
• 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.

33. “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

34. 11/10/2022 34
1955 1975 1995 2015 2035 2055
Better Building Blocks

35. References
• Araya D (2018) Augmented Intelligence: Smart Systems and the Future of Work and Learning. Peter Lang International Academic Publishers; 2018 Sep 28.
• Bush V (1945) As we may think. The Atlantic Monthly. 1945 Jul 1;176(1):101-8.
• Engelbart D (1962) Augmenting human intellect. Summary report AFOSR-3223 under Contract AF. 1962 Oct;49(638):1024.
• Gardner P, Maietta HN (2020) Advancing Talent Development: Steps Toward a T-Model Infused Undergraduate Education. Business Expert Press. URL:
https://www.amazon.com/Advancing-Talent-Development-Undergraduate-Education/dp/1951527062
• Kay A, Jobs S (1984) Wheels for the Mind. Apple Computer.
• Kline SJ (1995) Conceptual foundations for multidisciplinary thinking. Stanford University Press; 1995.
• Licklider JC (1960) . Man-computer symbiosis. IRE transactions on human factors in electronics. 1960 Mar(1):4-11.
• Malone TW (2018) Superminds: The surprising power of people and computers thinking together. Little, Brown Spark; 2018 May 15.
• Norman D (1994) Things that make us smart: Defending human attributes in the age of the machine. Diversion Books; 2014 Dec 2.
• Rouse WB, Spohrer JC (2018) Automating versus augmenting intelligence. Journal of Enterprise Transformation. 2018 Feb 7:1-21.
• Siddike MA, Spohrer J, Demirkan H, Kohda Y (2018) A Framework of Enhanced Performance: People's Interactions With Cognitive Assistants. International Journal
of Systems and Service-Oriented Engineering (IJSSOE). 2018 Jul 1;8(3):1-7.
• Spohrer JC (1998) Information in places. IBM Systems Journal. 1999;38(4):602-28.
• Spohrer JC, Engelbart DC (2004) Converging technologies for enhancing human performance: Science and business perspectives. Annals of the New York Academy
of Sciences. 2004 May;1013(1):50-82.
• Spohrer J, Siddike (2018) The Future of Digital Cognitive Systems: Tool, Assistant, Collaborator, Coach, Mediator. In Ed. Araya D. Augmented Intelligence: Smart
Systems and the Future of Work and Learning. Peter Lang International Academic Publishers; 2018 Sep 28.
• Spohrer J (2020) Online Platform Economy and Gig Workers: A USA Perspective. Presentation.
• Spohrer J & Maglio PP (2006) Service Science Management and Engineering (SSME): An Emerging Discipline. IBM Presentation.
11/10/2022 (c) IBM MAP COG .| 35

36. 36
What is a Responsible Service System Entity?
… customers/practitioners just name <your favorite provider>
… learners just name <your favorite role model>
Economics, Law, & Public Policy
Social & Behavioral Sciences
Design/
Cognitive Science
Systems
Engineering &
Human Factors
Operations
Computer Science/
Artificial Intelligence
Marketing
“a service system is a human-made system
to improve value co-creation interactions;
a dynamic configuration of resources
interconnected by value propositions.”
“service science is
the transdisciplinary study of
the evolving ecology of
responsible service systems entities
& their value-cocreation and
capability co-elevation
interactions.”
What is Service Science?
…researchers just name <your favorite discipline>
…educators just name <your favorite aha moment>