Fifth Digital Person Symposium Panel Discussion

1. 2022 Fifth Digital Person Symposium
Digital Person - Panel Session
Jim Spohrer
Retired IBM Executive
UDIP 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 Irene Ng for the opportunity
March 1, 2022 to moderate panel.
Highly recommend:
Humankind: A Hopeful History
By Dutch Historian, Rutger Bregman
<- Thanks
To Ray Fisk
For suggesting
this book

3. The Panelists
• Introducing the Panelists
• Professor Jon Crowcroft, FRS, FREng is the Marconi Professor of
Communications Systems in the Computer Laboratory of the University of
Cambridge and the Chair of the Programme Committee at the Alan Turing
Institute. Professor Jon Crowcroft is distinguished for his many seminal
contributions to the development of the Internet and is a fellow of
Wolfson College, Cambridge.
• Professor Irene Ng is Professor of Marketing and Service Systems, WMG,
University of Warwick and the CEO of Dataswift. Professor Irene Ng is also
a Turing Fellow and the creator of the Personal Data Account
infrastructure powered by the HAT Microserver. She specialises in market
design economics and service ecosystems and is the author of “Creating
New Markets in the Digital Economy” published by Cambridge University
Press.
• Professor Youngjin Yoo is the Elizabeth M. and William C. Treuhaft
Professor in Entrepreneurship and Professor of Information Systems at the
department of Design & Innovation at the Weatherhead School of
Management, Case Western Reserve University. An Association of
Information Systems Fellow, he is also WBS Distinguished Research
Environment Professor at Warwick Business School, UK. He is the founding
faculty director of xLab at Case Western Reserve University.
• Dr. Jim Spohrer is a retired IBM executive and on the board of directors of
the International Society of Service Innovation Professionals (ISSIP.org). He
specializes in service science and open-source trusted Artificial
Intelligence (AI).

4. Panel Description
• Jon Crowcroft (15 minutes): Digital
Identity & Trust: Cornerstones of the
Digital Economy
• Irene Ng (15 minutes): State of the
Digital Person: Progress, Challenges and
Opportunities
• Yongjin Yoo (15 minutes): The End of the
Beginning: The Emergence of Next-
Generation Digital Platforms
• Jim Spohrer (15 minutes): Q&A with
panelists
• All participants (30 minutes): Q&A with
panelists

5. Jon Crowcroft: Digital
Identity & Trust:
Cornerstones of the
Digital Economy
• Digital identity is a cornerstone of the digital economy and
hence requires very strong level of trust between
stakeholders. Foundational identity is typically a national
level affordance, and likely to be used only occasionally, to
bootstrap a number of functional identity services.
Bootstrapped functional identity services can then offer data
minimisation when supporting the authentication of user's
attributes (e.g., voter eligibility, age verification, access to
banking, medical services, travel between countries and so
on). Systems that allow users to enter the market with their
personal data from their personal data store need assurances
about the identity of those they trade with, and those others
need assurance about ownership and so on. Systems are
emerging that are distributed, federated and even
decentralised for identity, using similar architectures to the
personal data stores themselves. There are interesting
questions about how users will understand these systems,
and whether governments will adopt these systems, or they
will deploy and grow and flourish separately from national
authorities.
• Background reading:
https://www.turing.ac.uk/research/interest-
groups/trustworthy-digital-identity

6. Irene Ng: State of the
Digital Person: Progress,
Challenges and
Opportunities
• In this session, I will present the current state of affairs
for the Digital Person. First, I will provide the brief
overview of the goal - that of equity, justice and
freedoms accorded to the digital person. Towards that
goal, I will summarise the various pathways towards
the goal by diverse global communities and the way the
physical and the digital is now part of a blended
environment. I present the size of the prize and the
current players that aim to represent and control
digital persons. Broadly, representation of the digital
person is the battle for (1) the “potential” of the digital
person in data manifested through the need to collect
and store data - from identity data to other attribute
data through data architectures that are centralised,
decentralised, distributed and the hybrids and (2) the
“kinetic” value of data mobility signifying what the
digital person can or should be able to do both
physically and online safely, securely and smoothly
manifested in the design patterns of data flows and
finally (3) the “Agency” of the digital person in terms of
the support and assistance to the digital person
provided by computation, processing, AI, machine
learning. I present the current state of the digital
person, the progress in terms of funding, initiatives and
communities from research to innovation to markets;
the challenges faced by initiatives in different readiness
levels and the opportunities for everyone to get
involved.

7. Yongjin Yoo: The End of
the Beginning: The
Emergence of Next-
Generation Digital
Platforms
• The last twenty has seen remarkable economic growth through the
effective power of digital technology. With the combined market
capitalization of $10 billion and more, Apple, Amazon, Google and
Meta (formerly known as Facebook) who built their business
models around digital platforms would be the world's third-largest
economy only behind the US and China, if they were a country.
These platforms are all built on the combination of the layered
modular architecture of Web 2.0, the generativity of open
ecosystems, an unprecedented amount of digital trace data, and
powerful analytics capabilities using a centralized data
architecture. The proliferation of Web 2.0 platforms in the
economy, however, led to serious social, technical and economic
negative externalities due to (1) the fragmentation of the digital
identity of individuals and (2) privacy and data ownership
concerns. As new digital services and devices continue to develop,
the users' appetite for hyper-personal digital services will likely
continue to grow. While incumbent platform players are
introducing a number of solutions to address these externalities,
they are likely to fail unless they fundamentally re-architect the
way we think about the relationship between a person and the
increasingly-digitized world. In addition to the layers of hardware,
network, service, and content that defined the layered modular
architecture of Web 2.0 platforms, the digital identity and personal
data layers will likely emerge as the key battleground in the next
frontier. Decentralized, federated, decentralized and hybrid service
models will be powered by new digital identity and personal data
models. Unlike the current dominant layered modular architecture
of Web 2.0 that is a provider-centric view of users, the emergent
architecture of digital identity and personal data layers should
focus on persons as social actors, honoring their rights and agency.

8. Jim Spohrer:
Q&A with Panelists
• 1. How is the digital person being
connected to central bank digital
currency plans around the world,
and how might this help make
progress on UN Sustainable
Development Goals, including the
first goal which is to end poverty?
• 2. Is it possible to break free of
provider-centric digital person of
today?

9. Q&A with panelists
• Jon Crowcroft: Digital Identity &
Trust: Cornerstones of the Digital
Economy
• Irene Ng: State of the Digital Person:
Progress, Challenges and
Opportunities
• Yongjin Yoo: The End of the
Beginning: The Emergence of Next-
Generation Digital Platforms
• Jim Spohrer: Q&A with panelists
• All participants: Q&A with panelists

10. Background
• The premise of the Symposium as a unique cross-disciplinary environment for a robust discussion on
personal data and the “state of the digital person” from the perspectives of:
• • Digital personhood, law, freedom and democracy (humanities)
• Value, economics and markets (social science)
• Data analytics, data science and technology (science and technology)
• The theme for this year’s Symposium is The Empowered Digital Person: Global Projects with Data
Passports and Personal Data Servers, addressing the problem statement of equity and economic
justice, as well as how Personal Data infrastructure technology is now unlocking entire markets for
SMEs across verticals. In addition to the panel discussion on the digital person, the 5th Symposium will
also feature presentations on projects in our ecosystem that are leveraging personal data and data
portability to rapidly transform business models, and hopefully, entire verticals (You can read more in
this blogpost).
• Here are the links for the 2020 Symposium which was held online. The theme for 2020’s Symposium
was Digital Identity in a Post-Pandemic World, and the video recordings are of the three panel sessions
in the areas of humanities, social sciences (markets) and technology. The last link is to Irene’s state of
the HAT ecosystem presentation.
• https://www.dataswift.io/news/digital-person-symposium-digital-identity-in-humanities
https://www.dataswift.io/news/the-digital-person-symposium-digital-identity-in-economic-markets
https://www.dataswift.io/news/digital-identity-in-technology https://www.dataswift.io/news/video-
state-of-the-hat-ecosystem
• The Symposium will also feature global projects that are leveraging #dataportability to rapidly
transform business models, and we’ve been previewing these presentations through our pre-
Symposium conversations.

12. 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

13. Nations

14. Businesses

15. People

16. “AI won’t replace entrepreneurs, but entrepreneurs
who use AI will replace those who don’t.”
What does it mean to become a digital entrepreneur?

18. 18
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

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.
26-30 July 2015 3rd International Conference on The Human Side of Service Engineering
20
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. 4/5/2022 (c) IBM MAP COG .| 21
Arthur, W.B. Foundations of complexity economics. Nat Rev Phys (2021). https://doi.org/10.1038/s42254-020-00273-3

22. • 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

23. Timeline Future of AI: 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
23
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
OECD_Alistair Nolan to Everyone: “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.

24. Timeline: GDP/Employee
4/5/2022 (c) IBM 2017, Cognitive Opentech Group 24
(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

25. 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
4/5/2022 (c) IBM 2017, Cognitive Opentech Group 25
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

26. Service Science: Conceptual Framework
4/5/2022 (c) IBM MAP COG .| 26
Service Science

27. (c) IBM MAP COG .| 27
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)

28. “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

29. 4/5/2022 29
1955 1975 1995 2015 2035 2055
Better Building Blocks

30. 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
Better science
improves
understanding
Better logics
improve
interactions
Better
architectures
improve adaption
(change)
X+AI requires
investing
wisely to
improve
service
Where are the
better
models?
Technology Disciplines Minds Enterprise Minds + AI
Enterprise + AI
What type of
model?
Technology
System (T)
Quantitative &
Qualitative (I)
Mental Model in
Person (P)
Distributed
Organizational (O)
P+O+I+T
Service in the AI Era: Science, Logic, and Architecture Perspectives
(Spohrer, Maglio, Vargo, Warg – in progress)

31. Service Innovation Questions
• What real-world service system studied?
• What interaction process improved? How measured?
• What change process improved? How measured?
• Which stakeholders (responsible entities) benefitted?
How measured?
If you have concise and clear answers to these service innovation questions for your paper,
Then please consider applying for the ISSIP Excellence in Service Innovation Award
Recognition includes an ISSIP Digital Badge and opportunity for great visibility for the work.
Go to ISSIP.org website, recognition menu, second menu item - to learn more, and apply by filling out form

32. 4/5/2022 (c) IBM MAP COG .| 32
T-shaped Adaptive Innovator: Deep Problem-Solving and Broad Communication/Collaboration
Advanced Tech: AI to IoT to Quantum, GreenTech, RegTech, etc.
Work Practices: Agile, Service Design, Open Source
Mindset: Growth Mindset, Positive Mindset, Entrepreneurial
Many disciplines
Many sectors
Many regions/cultures
(understanding & communications)
Deep
in
one
sector
Deep
in
one
region/culture
Deep
in
one
discipline

33. Upskilling…
T-shaped
(l)earners
Gardner P, Maietta HN
(2020) Advancing Talent
Development: Steps
Toward a T-Model
Infused Undergraduate
Education.
Moghaddam Y, Demirkan
H, Spohrer J (2018) T-
Shaped Professionals:
Adaptive Innovators.

35. 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.
35
From 2002 - 2009, Jim co-founded
(with Paul Maglio) and directed
IBM Almaden Service Research
helping to establish service science,
applying science, technology,
and T-shaped upskilling of people to
business and societal transformation.
Who I am
2021 A big year: (1) hit 65, (2) career award, (3) retired from IBM

36. Who I am: Take 2
The Three Ages of Man (Giorgione)
Thanks to Alan Hartman for kind inspiration (slides) (recording) Service, when responsible entities apply their knowledge for mutual benefits
win-win/non-zero-sum games/value co-creation/capability co-elevation
Service is a central, fundamental concept of the value of systems interacting
(entities-interactions-outcomes)

37. 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