Community benefits for all

2. Benefits for All: Creating
Good Community Outcomes
Jim Spohrer
Director, IBM Cognitive OpenTech
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
Thanks to Katrine, Mac, Alex, and Cole for invitation to present
at Community Summit 2021 – May 11, 2021!
Three platforms/communities: People, Code, Information

3. Today’s Talk:
• Title: Benefits for All: Creating Good
Community Outcomes.
Abstract:
• Most people, businesses, universities,
governments aspire to transform into a better
future version of themselves.
• Communities help their members become better
future versions of themselves. Serving each other.
• Mastering new technologies is a transformation
sub-goal of most members - to learn to use
technologies to do something new or in new ways.
• Our IBM community members help each other
transform, according to the progression show me,
teach me, help me, do it for me, the first two are
usually free and the last two are usually for fee.
5/11/2021 (c) IBM MAP COG .| 3
Consumers and society at large are expecting
more from business. Embracing those
responsibilities can be good for shareholders, too.

4. Willie Tejada
IBM General Manager
ISV/Build Ecosystem &
Chief Developer Advocate
https://developer.ibm.com/callforcode/

5. https://lfaidata.foundation/
Ibrahim Haddad
VP Linux Foundation
LF AI & Data
Building Better Together Eminence

6. 6
Yassi Moghaddam
ISSIP Executive Director
Managing Director
Stradanet
Knowledge Sharing Eminence
http://issip.org/issip-discovery-summit-future-of-work-series-ai-automati-learning-series/

7. 5/11/2021 7
1955 1975 1995 2015 2035 2055
What will the the future of community be?

8. 5/11/2021 (c) IBM MAP COG .| 8

9. Trust: Two Communities
5/11/2021 IBM Code #OpenTechAI 9
Service
Science
Artificial
Intelligence
Trust:
Value Co-Creation
Responsible Entity Collaborators
Transdisciplinary Community
Trust:
Secure, Fair, Explainable
Machine Collaborators
Open Source Communities

10. 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
10
5/11/2021 (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

11. 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
5/11/2021 (c) IBM 2017, Cognitive Opentech Group 11
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

12. IA Progression – Tool, Assistant, Collaborator, Coach, Mediator
5/11/2021 (c) IBM MAP COG .| 12
Rouse & Spohrer (2018)
Siddike, Spohrer, Demirkan, Kodha (2018)
Araya (2018)
Spohrer& Siddike (2018)

13. 5/11/2021 13
1955 1975 1995 2015 2035 2055
Better Building Blocks

14. 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)

15. Today’s Talk:
• Title: Benefits for All: Creating Good Community
Outcomes.
Abstract: The 2020 pandemic is accelerating the
digital (information technologies)
transformation of society, including online
working, learning, playing and belonging. The
future of Artificial Intelligence (AI) will bring
even greater acceleration and transformations,
including Responsible Entities Learning. Service
science predicts that in this transformation of
business and society that competing for
collaborators will increasingly shape value co-
creation interactions and capability co-elevation
outcomes between responsible entities learning.
5/11/2021 (c) IBM MAP COG .| 15
Consumers and society at large are expecting
more from business. Embracing those
responsibilities can be good for shareholders, too.

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

17. Upskilling…
T-shapes (l)earners…
on multiple platforms
Rodgers S (2016) Jeremiah
Owyang on the Collaborative
Economy.
Kenny M, Zysman J (2016) The
Rise of the Platform Economy.

18. 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.

19. 19

20. Time - Session Speakers
8:00 - Welcome (10 minutes) ISSIP President, Ulf Vinneras (Aruba Networks, USA)
ISSIP Executive Director, Yassi Moghaddam (ISSIP, USA)
Event Chair/Contact, Jim Spohrer (IBM, USA) <spohrer@us.ibm.com>
Event Whitepaper Author, Ralph Badinelli (Virginia Tech, USA)
8:10 - First Panel (1 hr & 20 min)
Business Processes
Moderator /Chair opening (5 min) Rama Akkiraju (IBM, USA)
Speaker 1 (15 min) Jerry Cuomo (IBM, USA)
Speaker 2 (15 min) Marlon Dumas (U Tartu, Estonia)
Speaker 3 (15 min) Wil van der Aalst (U Aachen, Germany)
Speaker 4 (15 min) Vik Sohoni (McKinsey, USA)
Discussion (15 min)
9:30 - Break (10 minutes)
9:40 - Second Panel (1 hr & 20 min)
Digital Twins & Future Trends
Moderator/Chair opening (5 min) Terri Griffith (Simon Fraser U, Canada)
Speaker 5 (15 min) Shaun West (Lucerne U, Switzerland)
Speaker 6 (15 min) Hausi Muller (U Victoria, Canada)
Speaker 7 (15 min) Bob Cohen (Economics Institute, USA)
Speaker 8 (15 min) Erin Bishop-Rapacki (Robot Startups & Investing, USA)
Discussion (15 Min)
11:00 - Closing

21. Jim Spohrer, IBM
Director, Cognitive OpenTech
Jim Spohrer directs IBM’s open-source Artificial Intelligence developer
ecosystem effort. 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. He was CTO IBM
Venture Capital Group, co-founded IBM Almaden Service Research, and led IBM
Global University Programs. With over ninety publications and nine patents, he
received the 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 as LF AI Technical Advisory Board
Chairperson and ONNX Steering Committee Member (2020-2021).
5/11/2021 (c) IBM 2020, Cognitive Opentech Group 21

22. 5/11/2021
© IBM 2015, IBM Upward University Programs Worldwide
accelerating regional development
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Intelligence
Engineering Management Public
Policy
Education Design Humanities
Natural Systems (MIT)
Cognitive Systems (Yale)
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