DigitLab 20220511 v8.pptx

2022 DigitLab Discussions
Digital Transformation Accelerators:
A Service Science Perspective
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 Roger Maulll for the opportunity to discuss
Digital Transformation Accelerators and Service Science
Wednesday May 11, 2022, 14:00 BST UK, 06:00 PT USA
Highly recommend:
Humankind: A Hopeful History
By Dutch Historian, Rutger Bregman
<- Thanks
To Ray Fisk
For suggesting
this book, see
My summary here.

A Service Science Perspective on the Pandemic
and the Future of AI
• This talk explores digital transformation accelerators arising from two
shocks – the pandemic and the future of artificial intelligence (AI).
• The pandemic has accelerated the digital transformation of business and
society. Investments in AI also skyrocketed, including service robots and as-
a-service platforms, but future AI capabilities will likely be even more
transformative. Both of these shocks are examined from a service science
perspective. Service science is a two-decades old, emerging transdiscipline
that studies service systems, and responsible actors learning to invest
systematically in win-win interactions and change processes in business
and society.
• Service science helps to connect the growing abundance of data and
knowledge to value and benefits, including human values, human-centered
design, and importantly humanity-centered design.

Today’s Talk
• Understanding “service” is key.
• The pandemic accelerated the
digital transformation of
business and society.
• The “future of AI” is about to
accelerate the digital
transformation further.
• Our species' test – put simply -
is to achieve UN Sustainable
Development Goals.
Service is the the
application of resources
(e.g., knowledge) for the
benefit of another.
Service innovations
improve interaction and
change in business and
society. Service innovations
come in six main flavors.
The “future of AI” will be
responsible actors (service
system entities becoming
X+AI) learning to invest
systematically and wisely in
becoming better future
versions of themselves,
while inventing resilient
and equitable non-zero-
sum games.

Before Digital Transformation: Smarter Planet

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
14
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)

Service Science: Conceptual Framework
5/11/2022 (c) IBM MAP COG .| 15
Service Science

(c) IBM MAP COG .| 16
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)

IfM, IBM (2010)
Succeeding through
service innovation:
a service perspective
for education, research,
business and government.
University of Cambridge
Institute for Manufacturing,
Cambridge UK
2010

IBM’s Service Journey: A Summary Sketch
5/11/2022 (c) IBM MAP COG .| 19
Spohrer J (2017 ) IBM's service journey: A summary sketch. Industrial Marketing Management. 60:167-172.

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…
2022 Exploring ServCollab and ISSIP collaborations & forthcoming book
SSME 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

Bigger IA Trend in Human Time Usage & Skills
As smartphone apps grow up and people have 100 digital workers “earning” for them (owners) on platforms
• Hunter Gathers – local sourcing,
generalist
• Agriculture – local sourcing,
generalist – cities specialists
• Manufacturing – outsourcing to
production business, specialists
• Clothing to Shopping
• Service (pre-AI) – outsourcing to
service businesses, specialist
• Cooking to Restaurants
• Service (post-AI &
miniaturization) – insourcing, T-
shapes
• T-shaped (l)earners in platform
society, home again
5/11/2022 (c) IBM MAP COG .| 22
Spohrer & Maglio (2006) SSME, Slide #42
Spohrer (2020) Platform Economy
and Shift in Work

28
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

© 2011 IBM Corporation
IBM UP (University Programs) WW
29
L
Product-Service Systems as Learning Systems
Learning Systems
(“Life = Choices”)
Exploitation
(James March)
Run/Practice&Reduce
(IBM)
Operations Costs
Maintenance Costs
Incidence Planning &
Response Costs
(Insure)
Exploration
(James March)
Transform/Follow
(IBM)
Internal
External
Interactions
Innovate/Lead
(IBM)
Incremental
Radical
Super-Radical
“To be
the best,
learn from
the rest”
“Double
monetize,
internal win
and ‘sell’ to
external”
“Try to
operate
inside
the
comfort
zone”
Linda Sanford, IBM “Let Go To Grow”

30
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>

Future of AI
• What is the timeline for solving AI and IA?
• TBD: When can a CEO/anyone 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?
5/11/2022 (c) IBM 2020, Cognitive Opentech Group 31

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
32
5/11/2022 (c) IBM 2017, Cognitive Opentech Group
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

Timeline: GDP/Employee
(Source)
Lower compute costs translate into increasing productivity and GDP/employees for nations
Increasing productivity and GDP/employees should translate into wealthier citizens

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
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

Who is winning
https://www.technologyreview.com/s/608112/who-is-winning-the-ai-race/

Robots by Country
• Industrial robots per 10,000 people by country
5/11/2022 IBM #OpenTechAI 36
34

5/11/2022 (c) IBM MAP COG .| 37
The company says its first product, LettuceBot,
already has a hand in roughly 10 percent of US lettuce production.

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

AI Risks
• Job Loss
• Shorter term bigger risk
= de-skilling
• Super-intelligence
• Shorter term bigger risk
= bad actors

Other Technologies: Bigger impact? Yes.
• Augmented Reality (AR)/
Virtual Reality (VR)
• Game worlds
grow-up
• Blockchain/
Security Systems
• Trust and security
immutable
• Advanced Materials/
Energy Systems
• Manufacturing as cheap,
local recycling service
(utility fog, artificial leaf, etc.)

“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

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.

5/11/2022 (c) IBM MAP COG .| 43
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

5/11/2022 45
1955 1975 1995 2015 2035 2055
Better Building Blocks

10 million minutes of experience
5/11/2022 Understanding Cognitive Systems 46

2 million minutes of experience
5/11/2022 Understanding Cognitive Systems 47

Available by
Oct. 2022…
Martin Fleming
Former IBM Chief Economist
Jim Spohrer
Paul Maglio
Former IBM
Co-Founders Service Science

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.
51
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

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)

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

54
Service-dominant logic
 Service is the application of
competences for the benefit of
another entity
 Service is exchanged for
service
 Value is always co-created
 Goods are appliances for delivery
 All economies are service
economies
 All businesses are service
businesses
Vargo, S. L. & Lusch, R. F. (2004). Evolving to a new
dominant logic for marketing. Journal of Marketing, 68, 1 – 17.
Resource
Integrator/
Beneficiary
(“Firm”)
Resource
Integrator/
Beneficiary
(“Customer”)

55
What is value?
Value depends on the capabilities a system
has to survive and create beneficial change
in its environment.
Taking advantage of the service another
system offers means incorporating improved
capabilities.
Value can be defined as system
improvement in an environment.
All ways that systems work together to
improve or enhance one another’s
capabilities can be seen as being value
creating.
Vargo, S. L., Maglio, P. P., and Akaka, M. A. (2008). On value and value co-creation: A service
systems and service logic perspective. European Management Journal, 26(3), 145-152.

56
What is a service system?
Service involves at
least two entities
applying competences
and making use of
individual and shared
resources for mutual
benefit.
We call such
interacting entities
service systems.
A. Service Provider
• Individual
• Organization
• Public or Private
C. Service Target: The reality to be
transformed or operated on by A,
for the sake of B
• People, dimensions of
• Business, dimensions of
• Products, goods and material systems
• Information, codified knowledge
B. Service Client
• Individual
• Organization
• Public or Private
Forms of
Ownership Relationship
(B on C)
Forms of
Service Relationship
(A & B co-create value)
Forms of
Responsibility Relationship
(A on C)
Forms of
Service Interventions
(A on C, B on C)
Gadrey, J. (2002). The misuse of productivity concepts in services: Lessons from a comparison between
France and the United States. In J. Gadrey & F. Gallouj (Eds). Productivity, Innovation, and Knowledge in
Services: New Economic and Socio-economic Approaches. Cheltenham UK: Edward Elgar, pp. 26 – 53.
Spohrer, J., Maglio, P. P., Bailey, J. & Gruhl, D. (2007). Steps toward a
science of service systems. Computer, 40, 71-77.

57
Resources are the building blocks of service systems
Formal service systems can contract
Informal service systems can promise/commit
Trends & Countertrends (Evolve and Balance):
Informal <> Formal
Social <> Economic
Political <> Legal
Routine Cognitive Labor <> Computation
Routine Physical Labor <> Technology
Transportation (Atoms) <> Communication (Bits)
Qualitative (Tacit) <> Quantitative (Explicit)
First foundational premise
of service science
Service system entities
dynamically configure
four types of resources
The named resource is
Physical
or
Not-Physical
(physicists resolve disputes)
The named resource has
Rights
or
No-Rights
(judges resolve disputes
within their jurisdictions)
Physical
Not-Physical
Rights No-Rights
2. Technology
4.. Shared
Information
1. People
3. Organizations
Spohrer, J & Maglio, P. P. (2009) Service Science: Toward a Smarter Planet. In
Introduction to Service Engineering. Editors Karwowski & Salvendy. Wiley.
Hoboken, NJ..

58
Value propositions are the building blocks of service system networks
Second foundational premise
of service science
calculate value from multiple
stakeholder perspectives
A value propositions can
be viewed as a request from
one service system to another
to run an algorithm
(the value proposition)
from the perspectives of
multiple stakeholders according
to culturally determined
value principles.
The four primary stakeholder
perspectives are: customer,
provider, authority, and competitor
Stakeholder
Perspective
(the players)
Measure
Impacted
Pricing
Decision
Basic
Questions
Value
Proposition
Reasoning
1.Customer Quality
(Revenue)
Value
Based
Should we?
(offer it)
Model of customer: Do
customers want it? Is
there a market? How
large? Growth rate?
2.Provider Productivity
(Profit)
Cost
Plus
Can we?
(deliver it)
Model of self: Does it play
to our strengths? Can we
deliver it profitably to
customers? Can we
continue to improve?
3.Authority Compliance
(Taxes and
Fines)
Regulated May we?
(offer and
deliver it)
Model of authority: Is it
legal? Does it compromise
our integrity in any way?
Does it create a moral
hazard?
4.Competitor
(Substitute)
Sustainable
Innovation
(Market
share)
Strategic Will we?
(invest to
make it so)
Model of competitor: Does
it put us ahead? Can we
stay ahead? Does it
differentiate us from the
competition?
Value propositions coordinate & motivate resource access
Hoboken, NJ..

59
Access rights are the building blocks of service system ecology
(culture and shared information)
service = value-cocreation
B2B
B2C
B2G
G2C
G2B
G2G
C2C
C2B
C2G
***
provider resources
Owned Outright
Leased/Contract
Shared Access
Privileged Access
customer resources
Owned Outright
Leased/Contract
Shared Access
Privileged Access
OO
SA
PA
LC
OO
LC
SA
PA
S A
P C
Competitor Provider Customer Authority
value-proposition
change-experience
dynamic-configurations
(substitute)
time
Third foundational premise
of service science
reconfigure access rights to
resources by mutually agreed to
value propositions
 Access rights
 Access to resources that are owned
outright (i.e., property)
 Access to resource that are
leased/contracted for (i.e., rental car,
home ownership via mortgage,
insurance policies, etc.)
 Shared access (i.e., roads, web
information, air, etc.)
 Privileged access (i.e., personal
thoughts, inalienable kinship
relationships, etc.)
Hoboken, NJ..

60
Premises of service science: What service systems do
dynamically configure (transform)
four types of resources
calculate value from multiple
stakeholder perspectives
reconfigure access rights
to resources by mutually agreed
to value propositions
S A
P C
Physical
Not-Physical
Rights No-Rights
2. Technology
4.. Shared
Information
1. People
3. Organizations
Stakeholder
Perspective
Measure
Impacted
Pricing Questions Reasoning
1.Customer Quality Value
Based
Should we? Model of customer:
Do customers want
it?
2.Provider Productivity Cost
Plus
Can we? Model of self: Does
it play to our
strengths?
3.Authority Compliance Regulated May we? Model of authority:
Is it legal?
4.Competitor Sustainable
Innovation
Strategic Will we? Model of
competitor: Does it
put us ahead?
Hoboken, NJ..

IBM UP (University Programs) WW
61
Understanding the Human-Made World
See Paul Romer’s Charter Cities Video: http://www.ted.com/talks/paul_romer.html
Also see:
Symbolic Species, Deacon
Company of Strangers, Seabright
Sciences of the Artificial, Simon

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
63
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
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.

Timeline: GDP/Employee
(Source)
Lower compute costs translate into increasing productivity and GDP/employees for nations
Increasing productivity and GDP/employees should translate into wealthier citizens

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
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

5/11/2022 67
1955 1975 1995 2015 2035 2055
Better Building Blocks

“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?

5/11/2022 (c) IBM MAP COG .| 69
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

IA Progression – Tool, Assistant, Collaborator, Coach, Mediator
5/11/2022 (c) IBM MAP COG .| 71
Rouse & Spohrer (2018)
Siddike, Spohrer, Demirkan, Kodha (2018)
Araya (2018)
Spohrer& Siddike (2018)

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

• 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

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)

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

Intelligence Augmentation (IA) =
Socio-Technical Extension Factor on Capabilities
• Engelbart (1962)
• Spohrer & Engelbart (2002)
5/11/2022 (c) IBM MAP COG .| 87
Dedicated to Douglas E. Engelbart, Inventor
The Mouse (Pointing Device)
The Mother of All Demos
Bootstrapping Practice/Augmentation Theory
Note: Bush (1945) and Licklider (1960) created funding programs that benefitted Engelbart in building working systems.

IA as Socio-Technical Extension Factor on Capabilities & Values
IA (human values) is not AI (technology capability)
Difference 1: IA leads to more capable people even when scaffold removed
Difference 2: IA leads to more responsible people to use wisely the capabilities
5/11/2022 (c) IBM MAP COG .| 88
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)

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.
5/11/2022 (c) IBM MAP COG .| 89

Upskilling 2030:
Service Innovation Roadmaps and
Responsible Entities Learning
Jim Spohrer (IBM & ISSIP)
International Exploration of Service Science (IESS 2.1)
March 25, 2021

What is a SIR?
• Service Innovation Roadmap (SIR) is a kind of Business Model Canvas
(BMC) that responsible entities create for themselves to describe
three types of investments in learning/upskilling activities:
• Run: BMC for optimize activities (e.g., agile improvement method)
• Transform: BMC for copy activities (e.g., find role models)
• Innovate: BMC for invent activities (e.g., research, pilot, prove, monetize)
• Based on March (1991)
• March JG (1991) Exploration and exploitation in organizational learning.
Organization science. 1991 Feb;2(1):71-87.

5/11/2022 (c) IBM MAP COG .| 95
Arthur, W.B. Foundations of complexity economics. Nat Rev Phys (2021). https://doi.org/10.1038/s42254-020-00273-3

Write
Speak
Offer
Awards
Volunteers
ISSIP Platform Operations, Leadership Team, Supporters, Sponsors
International Society of Service Innovation Professionals (ISSIP.org)
“service innovations improve win-win interactions and change in business and society”
Join ISSIP to network with service innovation professionals and upcoming students,
while growing your knowledge sharing eminence about service systems/responsible actors,
in a non-profit professional association that promotes lifelong learning and T-shaped upskilling.
“everyone has something to learn, everyone has something to share”
Service – The application of resources (e.g., knowledge) for the benefit of another.
Service Innovations – Improvements in win-win interactions and change in business and society.
Win-Win– Service-for-service exchange, also called value co-creation interactions between actors.
Responsible Actors – individuals, businesses, universities, governments, also called service system entities.
Eminence – Professional reputation that comes from learning to invest more wisely in service innovations.
ISSIP helps members learn to invest more systematically in service innovations that matter.

ISSIP
International Society of Service Innovation Professionals Certifies that
Person
<Optional – Organization>
On Month Day, 2022 has been granted the
ISSIP <Type of Recognition> Award
for
<Explanation that appears in ISSIP Blog Post>
Terri Griffith, President Michele Carroll, Executive Director

Discovery Summit:
Future of
Expertise 1

Discovery Summit:
Future of
Expertise 2

Community
Progress
Update &
Board of
Directors Call
1H 2022

Community
Progress
Update &
Board of
Directors Call
2H 2022

ISSIP-DS1H2022: The Future of Expertise 1
• Three Layers
• Role – getting & staying hired (skills, experience, network, learning)
• Skills – ability to learn anything from T1 to T3 to T6 model
• Identity – full authentic self, many roles & skills
• Impact of AI: Fixed or Growth Mindset?
• Automated: AI can do it better than I; Will my boss hire an AI, instead of me?
• Augmented: I am better with my AI; Did I displace a person in my network?
• Connected to Survey on Digital Transformation of Responsible Actors
• Responsible Actors: Individual, Business, University, Government (AKA SSE)
• Digital Transformation: Digital Twin, Tools, Network

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

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