20220105 jim spohrer hicss v10

HICSS-55 Meeting:
Case studies of Artificial Intelligence, Business
Intelligence, Analytics Technologies for Industry
Platforms (Minitrack)
Jim Spohrer
Retired IBM
Member Board of Directors, ISSIP.org
Questions: spohrer@gmail.com
Twitter: @JimSpohrer
LinkedIn: https://www.linkedin.com/in/spohrer/
Slack: https://slack.lfai.foundation
Presentations on line at: https://slideshare.net/spohrer
Co-Chairs: Maarit Palo (IBM, Finland), Pekka Neittaanmaki
(UJyvaskyla, Finland), Jim Spohrer (IBM Retired, ISSIP.org, USA)
Highly recommend:
Humankind: A Hopeful History
By Dutch Historian, Rutger Bregman
<- Thanks
To Ray Fisk
For suggesting
this book

2
4:00pm CET/10:00amET/7:00am PT Session Co-Chair Welcome
4:05pm CET/10:05am ET/7:05am PT
Paper 4199- An Innovative Approach to Modeling Aviation Safety Incidents.pdf
Paper 3909 Utilizing Active Machine Learning for Quality Assurance- A Case Study of Virtual Car Renderings in the Automotive
Industry.pdf
Paper 3624- Automated Defect Detection of Screws in the Manufacturing Industry Using Convolutional Neural Networks.pdf
Paper 3289 Investigating the Role of Technical and Process Quality in Chatbots- A Case Study from the Insurance Industry.pdf
Paper 3063 An Empiricial Study of Factors Affecting Language-Independent Models.pdf
5:20pm CET/11:20am ET/8:20am PT General discussion, and more Q&A
5:30pm CET/11:30am ET/8:30am PT Final thank-you to all and end
HICSS-55 Meeting:
Minitrack: Case studies of Artificial Intelligence, Business Intelligence, Analytics Technologies for Industry Platforms[4]
Co-Chairs: Maarit Palo (IBM, Finland), Pekka Neittaanmaki (UJyvaskyla, Finland), Jim Spohrer (IBM Retired, ISSIP.org, USA)

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
3
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.

Intelligence Augmentation (IA) =
Socio-Technical Extension Factor on Capabilities
• Engelbart (1962)
• Spohrer & Engelbart (2002)
4/6/2022 4
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.

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

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
6
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)

4/6/2022 9
Skills Gap: From I-Shaped Employees to T-shaped Earners in a Platform Society
T-shaped Adaptive Innovator: Deep Problem-Solving and Broad Communication/Collaboration Capabilities
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
Vision: T-Shaped (L)Earners in platform society
with their hundreds of digital workers
creating multiple income streams

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
4/6/2022 10
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)

IA Progression – Tool, Assistant, Collaborator, Coach, Mediator
4/6/2022 11
Rouse & Spohrer (2018)
Siddike, Spohrer, Demirkan, Kodha (2018)
Araya (2018)
Spohrer& Siddike (2018)

Timeline: GDP/Employee
4/6/2022 12
(Source)
Lower compute costs translate into increasing productivity and GDP/employees for nations
Increasing productivity and GDP/employees should translate into wealthier citizens

“AI won’t replace entrepreneurs, but entrepreneurs
who use AI will replace those who don’t.”
Adapted from a Microsoft report, “The Future Computed”
Thanks to Tony Hey (Chief Data Scientist, Rutherford Appleton Lab, Harwell Campus, Didcot UK)

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
14
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

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.

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
4/6/2022 16
Spohrer & Maglio (2006) SSME, Slide #42
Spohrer (2020) Platform Economy
and Shift in Work

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.
4/6/2022 17

Service Science: Conceptual Framework
4/6/2022 (c) IBM MAP COG .| 18
Service Science

(c) IBM MAP COG .| 19
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)

“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

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."
4/6/2022 21

4/6/2022 22
1955 1975 1995 2015 2035 2055
Better Building Blocks

10 million minutes of experience
4/6/2022 Understanding Cognitive Systems 23

in 20 years
in 40 years
in 60 years
• Exascale (2060) = ~$1K
25
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

4/6/2022 26
What does it mean to become a digital entrepreneur?
Panel: Open Position Statement/Resources
• IBM Smarter Planet and University Programs (university-based startups) and
rethinking agriculture, manufacturing, and service sector
• Service Innovation (ISSIP.org) and Economic Development Report (World
Bank) and Upskilling Report (European Union)
• Phil Auerswauld’s book “The Coming Prosperity” (entrepreneurship) and
Kartik Gada’s book ”ATOM” (tech acceleration)
• Digital Entrepreneurship in the AI Era (100 digital workers for you)

4/6/2022 28
1955 1975 1995 2015 2035 2055

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.
29
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)

4/6/2022 (c) IBM MAP COG .| 32
T-shaped Adaptive Innovator: Deep Problem-Solving and Broad Communication/Collaboration
Many disciplines
Many sectors
Deep
in
one
sector
Deep
in
one
region/culture
Deep
in
one
discipline

4/6/2022 (c) IBM MAP COG .| 34
Minute 8:13 – “The train is leaving the station … and suddenly fear shifted to greed (fomo).”

in 20 years
in 40 years
in 60 years
• Exascale (2060) = ~$1K
35
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

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
36
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

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.
37
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

40
How responsible entities (service systems) learn and change over time
History and future of Run-Transform-Innovate investment choices
See Spohrer J (2021) Service Innovation Roadmaps and Responsible Entities Learning. IESS 2.1
URL: https://www.itm-conferences.org/articles/itmconf/pdf/2021/03/itmconf_iess2021_01001.pdf
• 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

Service Science: Conceptual Framework
4/6/2022 (c) IBM MAP COG .| 41
Service Science

(c) IBM MAP COG .| 42
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)

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.)
4/6/2022 (c) IBM 2017, Cognitive Opentech Group 44

Future of Service Science
Smarter and Wiser Service Systems - learning to invest better
Entities transform to better future versions of themselves by
inventing win-win games and competing for collaborators
Past Present Future
Organizational
Units
Family
Local Clan
Family
Business/Nation
Family
Platform Society
Change Individual
Generalist
(Breadth)
Individual
Specialist
(Depth)
Individual
T-shaped
(L)earners
Constant Competing for
collaborators:
win-win games
Competing for
collaborators:
win-win games
Competing for
collaborators:
win-win games
4/6/2022 (c) IBM MAP COG .| 47

4/6/2022 (c) IBM MAP COG .| 48
T-shaped Adaptive Innovator: Deep Problem-Solving and Broad Communication/Collaboration
Many disciplines
Many sectors
Deep
in
one
sector
Deep
in
one
region/culture
Deep
in
one
discipline

4/6/2022 50
1955 1975 1995 2015 2035 2055

Accelerating digital transformation and shift to robotics…
How will COVID-19 effect the need for and use of
robots in a service world with less physical contact?
Will robots improve or harm livelihoods/jobs?
Robots Rule Retail?
Taking away jobs
Telepresence Robot World?
Adding more jobs
Robots at Home?
Reducing need to have a job
T-shaped (L)earners
You will be assigned to a small team to discuss. Please have a team member to take notes of
the most important insights and/or questions that emerge from your discussion. Your notes
will be crucial for us to create a conference report, send to contact@creatingvalueconf.com
What is most probable to happen? What is desirable?
Spohrer

Timeline: GDP/Employee
4/6/2022 52
(Source)
Lower compute costs translate into increasing productivity and GDP/employees for nations
Increasing productivity and GDP/employees should translate into wealthier citizens

“AI won’t replace entrepreneurs, but entrepreneurs
who use AI will replace those who don’t.”
Adapted from a Microsoft report, “The Future Computed”
Thanks to Tony Hey (Chief Data Scientist, Rutherford Appleton Lab, Harwell Campus, Didcot UK)
What does it mean to become a digital entrepreneur?

Accelerating shift - from employees to earners in
platform society
Farrrel D, Grieg F (2014)
Online Platform
Economy.

IBM’s Service Journey: A Summary Sketch
4/6/2022 (c) IBM MAP COG .| 56
Spohrer J (2017 ) IBM's service journey: A summary sketch. Industrial Marketing Management. 60:167-172.

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

20220105 jim spohrer hicss v10

20220105 jim spohrer hicss v10

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