Solving disciplines 20200207 v2

Solving Disciplines: AI and Service Science
Jim Spohrer
Director, IBM Cognitive OpenTech
February 7, 2020
Presentations online at: http://slideshare.net/spohrer

Today’s Talk
• Thank-you for contributing to service
science
• AI – machines that solve tasks
• Disciplines & Professions
• Are these tasks? Yes.
• Service Science
• Original goal: A new discipline and profession
• Revised goal: Wisdom for rebuilding our
world
• Family as the oldest and most enduring service
system
2/7/2020 (c) IBM 2017, Cognitive Opentech Group 2
Abbot (2001) Abbot (1988)
Burgess & Locke (1945)

Thank-you for contributing to service science!
2/7/2020 (c) IBM MAP COG .| 3
Michel Leonard Joao Cunha Henriqueta Novoa Jorge Teixeira Lia Patricio Gerhard Satzger
Bob LuschSteve VargoPaul Maglio
Kazuyoshi Hidaka Monica DragoiceaTheodor Borangiu
Dan Berg Jim Tien

Sonae:
A nice welcome
to Porto 2020
2/7/2020 (c) IBM MAP COG .| 4

Trust: Two Communities
2/7/2020 IBM Code #OpenTechAI 5
Service
Science
Open Source
Trusted AI
Trust:
Value Co-Creation,
Transdisciplinary
Trust:
Fair, Secure, Explainable,
Open Communities
Special Issue
AI Magazine?
Handbook of
Open Source
Trusted AI?
Linux Foundation AI
Trusted AI Committee
https://wiki.lfai.foundation/display/DL/Trusted+AI+Committee
IBM CODAIT =
Center for Opensource Data and
Artificial Intelligence Technologies
https://developer.ibm.com/code/open/centers/codait/
ISSIP =
International Society of Service
Innovation Professionals
https://issip.org
IBM GitHub
AI Fairness 360 (AIF 360)
Adversarial
Robustness Toolbox (ART)
AI Explainability 360 (AIX360)
https://github.com/IBM/AIF360/
https://github.com/IBM/adversarial-robustness-toolbox
https://github.com/IBM/AIX360
Stanford Almond
https://almond.stanford.edu/
https://github.com/stanford-oval
Red Hat OpenDataHub
https://opendatahub.io/
Mozilla Common Voice
https://voice.mozilla.org/en
EU Service Science Expert Group
http://service-science.info/archives/5334

Narrow AI
Emerging
Broad AI
Disruptive and
Pervasive
General AI
Revolutionary
▼ We are here 2050 and beyond 6IBM Research AI © 2018 IBM Corporation
The evolution of AI
Borrowed from David Cox, IBM-MIT Lead
AI: The academic discipline that studies how to build machine capabilities that can
perform as well as or better than people can on the same task. Moving from single
narrow tasks (e.g., Chess) to multiple tasks (e.g., all types of natural language
processing and image understanding and robotics) to general AI (e.g., learning all
languages/social conventions/cultures, all academic disciplines, and all professions).
Who benefits:
(1) Entrepreneurs who
need digital workers
(2) Employers who need
augmented workers
and/or automation
(3) Customers who want
super-human service.

Timeline: Short History
2/7/2020
© IBM Cognitive Opentech Group (COG)
7
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.

10 million minutes of experience
2/7/2020 Understanding Cognitive Systems 8

2 million minutes of experience
2/7/2020 Understanding Cognitive Systems 9

10September 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
Larges Super Computer in the World,
= 13 MegaWatts of Power (HOT!)

11September 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!)

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
122/7/2020 (c) IBM 2017, Cognitive Opentech Group
2080204020001960
$1K
$1M
$1B
$1T
206020201980
+/- 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: Leaderboards FrameworkAI 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

Disciplines and Professions
Disciplines Professions
Definition (Wikipedia) "An academic discipline or field of study is a branch of
knowledge, taught and researched as part of higher
education. A scholar's discipline is commonly defined by the
university faculties and learned societies to which they
belong and the academic journals in which they publish
research. Disciplines vary between well-established ones
that exist in almost all universities and have well-defined
rosters of journals and conferences, and nascent ones
supported by only a few universities and publications. A
discipline may have branches, and these are often called sub-
disciplines.”
Disciplines cluster into: (1) Humanities, (2) Social Sciences,
(3) Natural Sciences, (4) Formal Sciences, (5) Applied
Sciences.
"A profession is an occupation founded upon specialized educational
training, the purpose of which is to supply disinterested objective
counsel and service to others, for a direct and definite
compensation... Major milestones which may mark an occupation
being identified as a profession include:[(1) an occupation becomes
a full-time occupation (2) the establishment of a training school, (3)
the establishment of a university school, (4) the establishment of a
local association, (5) the establishment of a national association of
professional ethics, (6) the establishment of state licensing laws.
Applying these milestones to the historical sequence of development
in the United States shows surveying achieving professional status
first, followed by medicine, actuarial science, law, dentistry, civil
engineering, logistics, architecture and accounting. With the rise of
technology and occupational specialization in the 19th century, other
bodies began to claim professional status: mechanical engineering,
pharmacy, veterinary medicine, psychology, nursing, teaching,
librarianship, optometry and social work, each of which could claim,
using these milestones, to have become professions by 1900. "
Service Science
Perspective
A type of service network made up of people in
roles in service systems (e.g., universities) that
responsibly maintain and extend a body of
knowledge for the purpose of earning a living
and transmission to future generations.
A type of service network made up of people in roles
in service systems (e.g., businesses) that responsibly
put into practice a body of knowledge on behalf of
customers for the purpose of earning a living and
contributing to society.
2/7/2020 (c) IBM MAP COG .| 14

Back to basics: Specialization -
Disciplines and Professions
(c) IBM MAP COG .|
• Spohrer J, McDavid D, Maglio PP,
Cortada JW (2006) NBIC
Convergence and Technology-
Business Coevolution: Towards a
Service Science to Increase
Productive Capacity. In Managing
nano-bio-info-cogno innovations,
eds. Bainbridge WS, Roco MC. NY:
Springer. Pp. 227-254.
• “Our perspective on the nature of
people is that people are creative
and productive. People invest their
time to capture value either from
exploiting known capabilities or in
creating new capabilities. James
March (1999) refers to this as the
exploitation (use old capability)
versus exploration (use new
capability) trade-off of systems
that learn and evolve.“
• “Civilization advances by extending
the number of important
operations which we can perform
without thinking of them.”
Alfred North Whitehead, English
mathematician
2/7/2020 15

Disciplines and Methodologies
• Brodie RJ, Löbler H, Fehrer JA (2019) Evolution of service-dominant logic: Towards a paradigm and
metatheory of the market and value cocreation?. Industrial Marketing Management. 79:3-12.
• “S-D logic references many different theories and methodologies, a situation
that implicitly assumes different philosophical perspectives or orientations,
notably objective, subjective and inter-subjective.
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Discipline Clusters Types of Phenomena Comment
Humanities Inter-Subjective History is partly objective
Social Sciences Subjective &
intersubjective
Psychology, parts objective
and parts subjective
Natural Sciences Objective Biology, parts evolve
Formal Sciences Objective Mathematics
Applied Sciences All Engineering & Technology,
Artificial Intelligence,
Service Science

SSME: Service Science, Management, and Engineering
IBM Research © 2006 IBM Corporation17
Back to Basics: What kinds of knowledge & skills should a service scientist have?
Academic disciplines evolving to combine technology, business, and social-organization
Technology
BusinessSocial-
Organizational
26
22
17 24
15
3
18
1
5
16
25 22. Inform. Sci & Sys
23. Service Ops & Mgmt
24. Service Engineering
25. Service Marketing
26. Social Complexity
27. Agent-based comput.
economics
28. Computational
Organization Theory
6. Managerial
Psychology
7. Human Capital
Management (HCM)
8. Organization Theory
9. Operations Research
10. Systems Engineering
11. Management Science
12. Game Theory
13. Industrial Engineering
14. Marketing
15. Computer &
Information Sciences
23
24
27
28
19
20
21
7
8
9
10
11
12
13
14
6
1990-2004
1960-1990
1900-1960
Before 1900
16. Management of
Innovation & Tech (MoT)
17. Experimental
Economics
18. AI & Games
19. Management of
Information Systems
20. Computer Supported
Collab. Work (CSCW)
21. Performance
Support Systems In
Business & Organization
1. Law
2. Political Economics
3. Education/Literacy
4. Sociology/History
5. Business
Administration (MBA)
Spohrer, J. and Maglio, P.P., 2008. The emergence of service science: Toward systematic
service innovations to accelerate co‐creation of value. Production and operations management, 17(3), pp.238-246.

Service Science: Why Now? IBM’s perspective
0
10
20
30
40
50
60
70
80
90
100
1982 1988 1994 1998 2003
Services
Software
Hardware
Other

Multidisciplinary Nature of
PhDs in IBM’s Global Services Division (US)
Engineering and Natural Sciences
Social Sciences
Business and Management
Liberal Arts and Humanities
Other

Need for service scientists in Research
PhDs in IBM’s Research Division (US)
Engineering and Natural Sciences
Social Sciences
Business and Management
Liberal Arts and Humanities
Other

Nation % WW
Labor
%
A
%
G
%
S
25 yr %
delta S
China 21.0 50 15 35 191
India 17.0 60 17 23 28
U.S. 4.8 3 27 70 21
Indonesia 3.9 45 16 39 35
Brazil 3.0 23 24 53 20
Russia 2.5 12 23 65 38
Japan 2.4 5 25 70 40
Nigeria 2.2 70 10 20 30
Banglad. 2.2 63 11 26 30
Germany 1.4 3 33 64 44
Top Ten Nations by Labor Force Size
(about 50% of world labor in just 10 nations)
A = Agriculture, G = Goods, S = Services
>50% (S) services, >33% (S) services
2004 2004
United States
The largest labor force migration
in human history is underway,
driven by urbanization,
global communications,
low cost labor, business growth
and technology innovation.
(A) Agriculture:
Value from
harvesting nature
(G) Goods:
Value from
making products
(S) Services:
Value from enhancing the
capabilities of things (customizing,
distributing, etc.) and interactions between things
The world is becoming a service system.
Why Now? Scale and speed of change!

Systems
Evolution
Complexity
Layers
Evolution Study & Rational Design
(coevolution of disciplines & jobs)
Natural
Systems
Physical 12-8B BB/Sun Physics – Lasers (physicist)
Chemical 4.5B Earth Chemistry - Dyes, Plastics (chemist)
Biological 3.5B Cells/DNA Biology, Genetics – Corn (biologist)
Neural 700M Clams… Neuroscience – Cochlea (neurologist)
Sociotechnical
or Human
Systems
Hunter-
Gathers
2M years ago Archeology, Anthropology - Stone Tools
(hunter, tool maker)
Agricultural 10K-5K years
(5 million people)
History - Irrigation, Towns, Cities
(specialization baker, miller, smith,...)
Industrial 250 years ago
(1 billon people)
Engineering, Economics, Law,
Education - Steam engine,
Democracy, Railroads (engineer)
Services 100 years ago
(2 billion people)
MBA, Social Sciences - Telephone,
Businesses (manager, employee)
Information
Services
50
(6 billion people)
Computer Science, Organization
Science - Computer, Internet
(consultant, consumer, shareholder)

IBM Research © 2006 IBM Corporation
IBM’s Service Journey: A Summary Sketch
2/7/2020
(c) IBM MAP COG .| 23
Spohrer J (2017)IBM's service journey: A summary sketch. Industrial Marketing Management. 60:167-72.

Computer Science
• "Computer science is the study of the phenomena surrounding computers. ... We
build computers and programs for many reasons. We build them to serve society
.... One of the fundamental contributions to knowledge of computer science has
been to explain, at a rather basic level, what symbols are. ... Symbols lie at the
root of intelligent action, which is, of course, the primary topic of artificial
intelligence. For that matter, it is a primary question for all of computer science.
For all information is processed by computer in the service of ends, and we
measure the intelligence of a system by its ability to achieve stated ends in the
face of variations, difficulties and complexities posed by the task environment.”
• Tenth Turing Awards Lecture: Allen Newell and Herbert A. Simon, “Computer
Science as Empirical Inquiry: Symbols and Search,”Communications of the ACM.
vol. 19, No. 3, pp. 113-126, March,1976. Available online at:
• https://www.cs.utexas.edu/~kuipers/readings/Newell+Simon-cacm-76.pdf
2/7/2020 (c) IBM MAP COG .| 24

Service-Dominant logic worldview and mindset
Year Publication Service Resource Integrators
2004 Vargo SL, Lusch RF (2004)
Evolving to a new dominant
logic for marketing. Journal of
marketing. 68(1):1-7.
The application of specialized skills
and knowledge is the fundamental
unit of exchange.
Operant resources are resources that
produce effects
2011 Vargo SL, Lusch RF (2011) It's
all B2B… and beyond: Toward
a systems perspective of the
market. Industrial marketing
management. 40(2):181-7.
The central concept in S-D logic is
that service — the application of
resources for the benefit of another
party — is exchanged for service
That is, all parties (e.g. businesses,
individual customers, households, etc.)
engaged in economic exchange are
similarly, resource-integrating, service-
providing enterprises that have the
common purpose of value (co)creation —
what we mean by “it is all B2B.”
2016 Vargo SL, Lusch RF.
Institutions and axioms: an
extension and update of
service-dominant logic.
Journal of the Academy of
Marketing Science. 2016 Jan
1;44(1):5-23.
value creation can only be fully
understood in terms of integrated
resources applied for another
actor’s benefit (service) within a
context, including the institutions
and institutional arrangements that
enable and constrain value creation.
To alleviate this limitation and facilitate a
better understanding of cooperation (and
coordination), an eleventh foundational
premise (fifth axiom) is introduced, focusing
on the role of institutions and institutional
arrangements in systems of value
cocreation: service ecosystems.2/7/2020 (c) IBM MAP COG .| 25

Service Science the study of service systems entities
Year Publication Service Science Service System
2007 Spohrer J, Maglio, PP, Bailey J,
Gruhl, D (2007) Steps toward
a science of service
systems, IEEE Computer,
(40)1:71-77.
Services science is an emerging field
that seeks to tap into these and
other relevant bodies of knowledge,
integrate them, and advance three
goals—aiming ultimately to
understand service systems, how
they improve, and how they scale.
The components of a service system are
people, technology, internal and external
service systems connected by value
propositions, and shared information (such
as language, laws, and measures.
2008 Spohrer, J, Vargo S, Caswell N,
Maglio PP (2008) The service
system is the basic abstraction
of service science, HICSS-41,
NY: IEEE Press, Pp. 1-10.
Service science is the study of the
application of the resources of one
or more systems for the benefit of
another system in economic
exchange.
Informally, service systems are
collections of resources that can
create value with other service systems
through shared information.
2008 Maglio PP, Spohrer J (2008)
Fundamentals of service
science. Journal of the
academy of marketing
science. 36(1):18-20.
Service science is the study of
service systems, aiming to create a
basis for systematic service
innovation.
Service systems are value-co-creation
configurations of people, technology, value
propositions connecting internal and
external service systems, and shared
information (e.g., language, laws, measures,
and methods).2/7/2020 (c) IBM MAP COG .| 26

Service Science the study of service system entities
2/7/2020 (c) IBM MAP COG .| 27
2009 Spohrer J, Maglio PP (2009)
Service science: Toward a
smarter planet. In
Introduction to service
engineering, Eds. Karwowski
and Salvendy. Pp. 3-10
Service science is a specialization of
systems science. So service science
seeks to create a body of knowledge
that accounts for value-cocreation
between entities as they interact…
Service system entities are dynamic
configurations of resources. As described
below, resources include people,
organizations, shared information, and
technology.
2012 Spohrer J, Piciocchi P, Bassano
C (2012) Three frameworks
for service research: exploring
multilevel governance in
nested, networked systems.
Service Science. 4(2):147-160.
SSME+D is built on top of the
Service-Dominant logic (SD Logic)
worldview
A service system entity is a dynamic
configuration of resources (at least one of
which, the focal resource, is a person with
rights).
2013 Spohrer J, Giuiusa A,
Demirkan H, Ing D (2013)
Service science: reframing
progress with universities.
Systems Research and
Behavioral Science. 30(5):561-
569
Service science is an emerging
branch of systems sciences with a
focus on service systems (entities)
and value cocreation (complex non-
zero-sum interactions).
… complex adaptive entities - service
systems - within an ecology of nested,
networked entities… From a service science
perspective, progress can be thought of in
terms of the rights and responsibilities of
entities

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2014 Spohrer J, Kwan SK, Fisk RP
(2014)Marketing: a service sci
ence and arts perspective,
Handbook of Service Market
ing Research, Eds. Rust RT,
Huang MH, NY:Edward Elgar,
pp. 489-526.
Service science (short for Service
Science, Management, Engineering,
Design, Arts, and Public Policy) is an
emerging transdiscipline for the (1)
study of evolving service system
entities and value co-creation
phenomena, as well as (2) pedagogy
for the education of 21st century T-
shaped service innovators from all
disciplines, sectors, and cultures.
So like all early stage scientific
communities, the language for talking
about service systems and value co-creation
phenomena continues to evolve. … Service
system entities are economic and social
actors, which configure (or integrate)
resources. … A formal service system entity
(SS-FSC3) is a legal, economic entity with
rights and responsibilities codified in
written laws.
2015 Spohrer J, Demirkan H,
Lyons (2015) Social Value: A
Service Science Perspective.
In: Kijima K. (eds) Service
Systems Science. Translational
Systems Sciences, vol 2.
Tokyo: Springer. Pp. 3-35.
transdiscipline for the (1) study of
evolving service system entities and
value co-creation phenomena and
(2) pedagogy for the education of
twenty-first-century T-shaped
service innovators from all
disciplines, sectors, and cultures
Formal service system entities (as opposed
to informal service system entities) can be
ranked by the degree to which they are
governed by written (symbolic) laws and
evolve to increase the percentage of their
processes that are explicit and symbolic.

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2016 Spohrer J (2016) Services
Science and Societal
Convergence. In W.S.
Bainbridge, M.C. Roco
(eds.),Handbook of Science
and Technology Convergence,
pp. 323-335
transdiscipline for the (1) study of
evolving ecology of nested,
networked service system entities
and value co-creation phenomena,
as well as (2) pedagogy for the
education of the twenty-first-
century T-shaped (depth and
breadth) service innovators from all
disciplines, sectors, and cultures.
As service science emerges, we can begin
by “seeing” and counting service system
entities in an evolving ecology, working to
“understand” and make explicit their
implicit processes of valuing …
2016 Spohrer J (2016) Innovation
for jobs with cognitive
assistants: A service science
perspective, In Disrupting
Unemployment ,
Eds. Nordfors, Cerf,
Seng, Missouri: Ewing Marion
Kauffman Foundation, Pp.
157-174.
Service science is the emerging
transdiscipline that studies the
evolving ecology of nested,
networked service system entities,
their capabilities, constraints, rights,
and responsibilities.
There are perhaps twenty billion formal
service system entities in the world today,
each governed in part by formal written
laws. Every person, household, university,
business, and government is a formal
service system entity, but my dog, my
smartphone, and my ideas are not.

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2017 Spohrer J, Siddike MAK,
Kohda Y (2017) Rebuilding
evolution: a service science
perspective. HICSS 50.
Service science is the study of the
evolving ecology of service system
entities, complex socio-technical
systems with rights and
responsibilities – such as people,
businesses, and nations.
Service systems are dynamic configurations
of people, technology, organization and
information that interact through value
proposition and co- create mutual value.
2019 Pakalla D, Spohrer J (2019,
forthcoming) Digital Service:
Technological Agency in
Service Systems. HICSS 52.
For the purposes of this paper,
service science can be summarized
as the study of the evolving ecology
of service system entities, their
capabilities, constraints, rights, and
responsibilities, including their
value co-creation and capability co-
elevation mechanisms .
Service systems are a type of socio-
technical system, such as people,
businesses, and nations, all with unique
identities, histories, and reputations based
on the outcomes of their interactions with
other entities.

Service Science: Conceptual Framework
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32
Service system entities configure four types of
resources
• First foundational premise of service
science:
• Service system entities dynamically
configure
four types of resources
• Resources are the building
blocks of entity architectures
• Named resources are:
• Physical or
• Not-Physical
• Physicist resolve disputes
• Named resources have:
• Rights or
• No Rights
• Judges resolve disputes
Spohrer, J & Maglio, P. P. (2009)
Service Science: Toward a Smarter Planet.
In Introduction to Service Engineering.
Editors Karwowski & Salvendy. Wiley. Hoboken, NJ..
Physical
Not-Physical
Rights No-Rights
2. Technology/
Environment
Infrastructure
4. Shared
Information/
Symbolic
Knowledge
1. People/
Individuals
3. Organizations/
Institutions
Formal service systems can contract to configure resources/apply competence
Informal service systems can promise to configure resources/apply competence
Trends & Countertrends (Balance Chaos & Order):
(Promise) Informal <> Formal (Contract)
(Relationships & Attention) Social <> Economic (Money & Capacity)
(Power) Political <> Legal (Rules)
(Evolved) Natural <> Artificial (Designed)
(Creativity) Cognitive Labor <> Information Technology (Routine)
(Dance) Physical Labor <> Mechanical Technology (Routine)
(Relationships) Social Labor <> Transaction Processing (Routine)
(Atoms) Transportation <> Communication (Bits)
(Tacit) Qualitative <> Quantitative (Explicit)
(Secret) Private <> Public (Shared)
(Anxiety-Risk) Challenge <> Routine (Boredom-Certainty)
(Mystery) Unknown <> Known (Justified True Belief)

33
Service system entities calculate value from multiple stakeholder perspectives
• Second foundational premise of service
science
• Service system entities calculate value
from multiple stakeholder perspectives
• Value propositions are the building
blocks of service networks
• 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
• Citizens: special customers
• Entrepreneurs: special providers
• Parents: special authority
• Criminals: special competitors
Spohrer, J & Maglio, P. P. (2009) Service Science: Toward a Smarter Planet. In Introduction to
Service Engineering. Editors Karwowski & Salvendy. Wiley. Hoboken, NJ..
Model of competitor: Does
it put us ahead? Can we
stay ahead? Does it
differentiate us from the
competition?
Will we?
(invest to
make it so)
StrategicSustainable
Innovation
(Market
share)
4.Competitor
(Substitute)
Model of authority: Is it
legal? Does it compromise
our integrity in any way?
Does it create a moral
hazard?
May we?
(offer and
deliver it)
RegulatedCompliance
(Taxes and
Fines, Quality
of Life)
3.Authority
Model of self: Does it play
to our strengths? Can we
deliver it profitably to
customers? Can we
continue to improve?
Can we?
(deliver it)
Cost
Plus
Productivity
(Profit,
Mission,
Continuous
Improvement,
Sustainability)
2.Provider
Model of customer: Do
customers want it? Is there
a market? How large?
Growth rate?
Should we?
(offer it)
Value
Based
Quality
(Revenue)
1.Customer
Value
Proposition
Reasoning
Basic
Questions
Pricing
Decision
Measure
Impacted
Stakeholder
Perspective
(the players)
Value propositions coordinate & motivate resource access

34
Service system entities reconfigure access rights to resources by mutually agreed to value
propositions
• Third foundational premise of service science
• Service system entities reconfigure access
rights to resources by mutually agreed to value
propositions
• Access rights are the building blocks of the
service ecology (culture and information)
• 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.)
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 AP C
Competitor Provider Customer Authority
value-proposition
change-experience
dynamic-configurations
(substitute)
time
Spohrer, J & Maglio, P. P. (2009)
Service Science: Toward a Smarter Planet.
In Introduction to Service Engineering.
Editors Karwowski & Salvendy. Wiley. Hoboken, NJ..

35
Service system entities interact to create ten types of outcomes
• Four possible outcomes from a two player
game
• ISPAR generalizes to ten possible
outcomes
• win-win: 1,2,3
• lose-lose: 5,6, 7, maybe 4,8,10
• lose-win: 9, maybe 8, 10
• win-lose: maybe 4
lose-win
(coercion)
win-win
(value-cocreation)
lose-lose
(co-destruction)
win-lose
(loss-lead)
WinLose
Provider
Lose Win
Customer
ISPAR descriptive model
Maglio PP, SL Vargo, N Caswell, J Spohrer: (2009) The service system is the basic abstraction of service science. Inf. Syst. E-Business Management 7(4): 395-406 (2009)

36
Service system entities learn to systematically exploit technology:
Technology can perform routine manual, cognitive, transactional work
L
“To be
the best,
learn from
the rest”
“Double
monetize,
internal win
and ‘sell’ to
external”
“Try to
operate
inside
the
comfort
zone”
March, J.G. (1991) Exploration and exploitation in organizational learning. Organizational Science. 2(1).71-87.
Sanford, L.S. (2006) Let go to grow: Escaping the commodity trap. Prentice Hall. New York, NY.

37
Service system entities are physical-symbol
systems
• Service is value cocreation.
• Service system entities reason
about value.
• Value cocreation is a kind of
joint activity.
• Joint activity depends on
communication and
grounding.
• Reasoning about value and
communication are (often)
effective symbolic processes.
Newell, A (1980) Physical symbol systems, Cognitive Science, 4, 135-183.
Newell, A & HA Simon(1976). Computer science as empirical inquiry: symbols and search. Communications of the ACM, 19, 113-126.

38
Summary
Spohrer, J & Maglio, P. P. (2009) Service Science: Toward a Smarter Planet. In Introduction to Service Engineering. Editors Karwowski & Salvendy. Wiley. Hoboken, NJ..
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)
Model of competitor:
Does it put us ahead?
Will we?StrategicSustainable
Innovation
4.Competitor/
Substitutes
Model of authority: Is
it legal?
May we?RegulatedCompliance3.Authority
Model of self: Does it
play to our strengths?
Can we?Cost
Plus
Productivity2.Provider
Model of customer:
Do customers want
it?
Should we?Value
Based
Quality1.Customer
ReasoningQuestionsPricingMeasure
Impacted
Stakeholder
Perspective
2. Value from stakeholder perspectives
S AP C
3. Reconfigure access rights
4. Ten types of outcomes (ISPAR)
5. Exploit information & technology
6. Physical-Symbol Systems

39
Service Science: Transdisciplinary Framework to Study Service Systems
Systems that focus on flows of things Systems that governSystems 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)

Brian Arthur - Economist
• The term “technological unemployment” is from John Maynard Keynes’s 1930 lecture,
“Economic possibilities for our grandchildren,” where he predicted that in the future, around
2030, the production problem would be solved and there would be enough for everyone, but
machines (robots, he thought) would cause “technological unemployment.” There would be
plenty to go around, but the means of getting a share in it, jobs, might be scarce. We are not quite
at 2030, but I believe we have reached the “Keynes point,” where indeed enough is produced by
the economy, both physical and virtual, for all of us. (If total US household income of $8.495
trillion were shared by America’s 116 million households, each would earn $73,000, enough for
a decent middle-class life.) And we have reached a point where technological unemployment is
becoming a reality. The problem in this new phase we’ve entered is not quite jobs, it is access to
what’s produced. Jobs have been the main means of access for only 200 or 300 years. Before
that, farm labor, small craft workshops, voluntary piecework, or inherited wealth provided access.
Now access needs to change again. However this happens, we have entered a different phase for
the economy, a new era where production matters less and what matters more is access to that
production: distribution, in other words—who gets what and how they get it. We have entered
the distributive era.
2/7/2020 IBM #OpenTechAI 40

Disciplines and some of the key entities they study
2/7/2020 (c) IBM MAP COG .| 41
Computer Science: Physical Symbol System Entities
AI: Digital Cognitive System Entities
Chemistry: Auto-Catalytic Molecular System Entities
Biology: Biological Cognitive System Entities
Service science: Service system entities
Service science studies the evolving ecology
of service system entities,
their capabilities, constraints, rights, and responsibilities
their value co-creation and
capability co-elevation interactions, as well as
their outcome identities and reputations.

Service Research
• Artificial Intelligence in Service
• "The theory specifies four intelligences required for service tasks—mechanical,
analytical, intuitive, and empathetic—and lays out the way firms should decide
between humans and machines for accomplishing those tasks.”
• Huang MH and Rust RT (2018) Artificial Intelligence in Service. Journal of
Service Research. 21(2):155–172.
• Customer Acceptance of AI in Service Encounters: Understanding
Antecedents and Consequences
• "expand the relevant set of antecedents beyond the established constructs and
theories to include variables that are particularly relevant for AI applications
such as privacy concerns, trust, and perceptions of “creepiness.”
• Ostrom AL, Foheringham D, Bitner MJ (2018, forthcoming) Customer
Acceptance of AI in Service Encounters: Understanding Antecedents and
Consequences. In Handbook of Service Science, Volume 2, Eds, Maglio,
Kieliszewski,Spohrer,Lyons,Patricio,Sawatani. New York: Springer. Pp. x-y.
2/7/2020 (c) IBM MAP COG .| 42

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.
2/7/2020 43
Take free online cognitive classes today at cognitiveclass.ai

2/7/2020
© IBM 2015, IBM Upward University Programs Worldwide
accelerating regional development
44
I have…
Have you noticed how the building blocks just
keep getting better?

Learning to program:
My first program
2/7/2020
45
Early Computer Science Class:
Watson Center at Columbia 1945
Jim Spohrer’s
First Program 1972

2/7/2020
© IBM UPWard 2016
46
Fast Forward 2016:
Consider this…

Microsoft CaptionBot June 19, 2016
2/7/2020
© IBM UPWard 2016
47

Microsoft CaptionBot June 20, 2016
2/7/2020
© IBM UPWard 2016
48

IBM Image Tagging
2/7/2020
© IBM UPWard 2016
49

Today: November 10, 2017
2/7/2020
© IBM DBG COG 2017
50
IBM

Raise your
hand, if you
are >50%
sure you
know what
type of leaf
this is….
2/7/2020 (c) IBM MAP COG .| 51

October 3, 2018: Uploaded…
2/7/2020 (c) IBM MAP COG .| 52

2/7/2020
53
Cognitive Mediators
for all people in all roles

Occupations = Many Tasks
2/7/2020
54

Watson Discovery Advisor
2/7/2020
55
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/

Data Scientists, AI Model Builder
• “In one of those rooms, Vladimir Iglovikov, one of the “grandmasters” at the top of Kaggle’s rankings, stood by to offer tips
to competitors who needed help. He credits Kaggle with helping him rise from crunching data at a collection agency to
working on vision systems for self-driving cars at Lyft—an example of how the site’s top performers can find their lives
transformed by the skills and cachet won in competition. … The competitors toiled in the shadow of a leaderboard
projected onto a large screen. Kagglers gauge their progress during a competition by submitting code to the site for
testing, and receive a score that’s posted publicly. … Not long after 11 am, about two hours into the contest, the AutoML
team submitted its first auto-generated code—and debuted in second place on the leaderboard.”
2/7/2020 (c) IBM MAP COG .| 56

“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

2/7/2020 58
1955 1975 1995 2015 2035 2055
Better Building Blocks

Smartphones pass entrance exams? When?
… when will
your smartphone
be able to take and
pass any online
course? And then
be your coach, so
you can pass too?

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.

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.

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."

Question: How would you rebuild your
discipline from scratch?
• Some disciplines renew themselves [Tuure Tuunanen]
2/7/2020 (c) IBM MAP COG .| 63

2/7/2020
64
Brief History of Knowledge and Making: Personbyte and Peoplebyte

What can one person know and make?
2/7/2020
65

The Maker Movement &
Open Source Ecology
2/7/2020
66

So what does this have to do with programming
and computation?
2/7/2020
67
Both Turing and von Neumann dreamed of universal machines and constructors

Rewinding
Evolution
• Spohrer J, Giuiusa A,
Demirkan H, Ing D (2013)
Service science:
reframing progress with
universities. Systems
Research and Behavioral
Science. 30(5):561-569.

Why rebuilding evolution? Better Education
• If there be an order in which
the human race has mastered
its various kinds of
knowledge, there will arise in
every child an aptitude to
acquire these kinds of
knowledge in the same
order.... Education is a
repetition of civilization in
little.[28]
• — Herbert Spencer
http://www.slideshare.net/spohrer/spohrer-icer-20150810-v1

Sciences provide…
• Frameworks for people to ask and answer questions
systematically
• Explanations with instructions on “how to re-do”
2/7/2020
71
Kline: Conceptual Foundation of Multidisciplinary Thinking -
“To our children and children’s children,
to whom we elders owe an explanation of the world
that is understandable, realistic, forward-looking, and whole.”
Proenneke:
Alone in the Wilderness -
To do a thorough testing,
should each generation
be required to rapidly rebuild
from scratch?
A re-makers movement?

Resilience:
Rapidly Rebuilding From Scratch
• Dartnell L (2012) The Knowledge: How to
Rebuild Civilization in the Aftermath of a
Cataclysm. Westminster London: Penguin
Books.

2/7/2020
74

In Summary: Augmented intelligence
with automation of tasks, rebuilding
wisdom required
2/7/2020
75
“A service science
perspective considers
the evolving ecology of
service system entities,
their value co-creation and
capability co-elevation
interactions, and their
capabilities, constraints,
rights, and responsibilities.”
Cognitive Systems
Entities
Service
Systems
Entities With
Cognitive
Mediators
Add Rights &
Responsibilities

2/7/2020
76
Physics Chemistry Biology
Neuroscience Psychology Artificial
Intelligence
Engineering Management Public
Policy
Education Design Humanities
Natural Systems
Cognitive Systems
Service Systems
My life from
Undergraduate
To Graduate
To Professional

2/7/2020 (c) IBM MAP COG .| 77
Come visit us at IBM Reseach – Almaden in California
Watson West – San Francisco

Solving disciplines 20200207 v2

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