The document summarizes an ISSIP Discovery Summit on the future of expertise held on June 29, 2022. The summit included two panels on the future of expertise moderated by Jim Spohrer. Panel 1 included speakers from IBM, Mastercard, APQC, and NSF who discussed industry and government perspectives on the future of expertise. Panel 2 included speakers from Amazon, UC Santa Cruz, Simon Fraser University, and UFMG who discussed topics like analytic thinking, industry skills needs, systems thinking, and tacit knowledge management. The agenda and speakers for the event are provided.

1. ISSIP Discovery Summit:
Future of Expertise 1
June 29, 2022

2. Welcome
Michele Carroll (LI)
ISSIP Executive Director
Founder & President
Carrollco
Marketing Services
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Discovery Summit: Future of Expertise 1
Today’s Agenda (next slide)
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statement to the whitepaper
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innovation that benefits business, economy, and society.

3. Today’s Agenda:
Future of Expertise
Michele Carroll (LI)
Executive Director, ISSIP
Panel 1 Moderator: Jim Spohrer (ISSIP) - 8:10-9:20am Pacific Time (USA)
Utpal Mangla (IBM) “An Industry Perspective”
Heather Yurko (Mastercard) “Finding Expertise”
Cindy Huber (APQC) “Knowledge Mgmt , AI and an APQC Perspective”
Alexandra Medina-Borja (NSF) “An NSF/Government Perspective”
Panel 2 Moderator: Jim Spohrer (ISSIP) - 9:30-10:40am Pacific Time (USA)
Haluk Demirkan (Amazon) “Analytic Thinking and Adaptive Innovators”
Yassi Moghaddam (UCSC) “Industry Future Skills Needs”
Terri Griffith (Simon Fraser) “Systems Savvy - Thinking in 5T™”
Rodrigo Ribeiro (UFMG, Brazil) “Tacit Knowledge Management”

4. ISSIP
President’s
Welcome
Terri Griffith (LI)
Simon Frasier University,
Keith Beedie Chair in
Innovation and Entrepreneurship,
Professor, Author

5. Jim Spohrer (LI)
Retired Industry Executive,
and ISSIP event organizer
Future of Expertise
Panel 1: Introduction

6. Jim Spohrer (LI)
Retired Industry Executive,
and ISSIP event organizer
Future of Expertise
Panel 1: Introduction
The future of expertise encapsulates a wide range of topics.
Industry struggles to hire the adaptive talent needed to keep up with accelerating
demand for offerings and to digitally transform operations and ecosystems.
Universities struggle to successfully graduate diverse individuals with needed skills,
experience, and mindsets to hit-the-ground-running and succeed,
even as some question the need for a university education.
Governments realize that the sustainable wealth of nations depends on high-skill,
high-pay, highly-engaged workers within their borders.
Simultaneously, individuals are faced with a dizzying array of “opportunities” to upskill
for more pay, but often are unable to decide which path might have the best
return-on-investment for their careers and quality-of-life.
New technologies and a host of disruptive existing and impending world events,
only add to the complexity of this important topic – the future of expertise.
More than a single skillset (stock of deep knowledge),
lifelong learning (knowledge flows) and integration are key to the future of expertise.

7. Jim Spohrer (LI)
Retired Industry Executive,
and ISSIP event organizer
Future of Expertise
Panel 1: Introduction
Competence - as learned and perpetuated by communities.
Expertise - as legitimated competence, therefore institutions matter too.

8. Jim Spohrer (LI)
Retired Industry Executive,
and ISSIP event organizer
Future of Expertise
Panel 1: Introduction
100 position statements summarized into 10 predictions (see whitepaper DRAFT):
1. People collaborating with AI (Artificial Intelligence) machines as the new normal
2. Lifelong learning to constantly grow the breadth and depth of skills and other
capabilities (T-shaped metaphor and beyond)
3. A race to keep up with the latest in-demand “hot” skill sets
4. Social-emotional intelligence will increasingly be the key to success,
which may include a mature corporate citizenship skill set
5. Data-driven science-based development of expertise for individuals, cities, countries
6. The rise of collective or swarm intelligence
7. Responsible actors and their AI/digital twins collaborating in trusted networks,
all learning to invest systematically in becoming better future versions of themselves
8. Learning-unlearning-adapting to accelerating change
9. It’s over; dead; simply at the mercy of vested interests, unless we find a new way to
re-establish trust in true expertise (versus everyone’s opinion is weighted by
how much money, power, influence they have over others)
10. Not exactly like the past, and while impossible to predict with any precision,
surely some blend of the traditional college graduate education expertise,
entrepreneurial and technology-maker expertise, business, government, sports, art, media,
political influencer expertise, and perhaps a few new types of expertise emerging, such as AI, as well.

9. Most agreement
Least agreement

10. Middle of the Pack

11. An Industry Perspective on
the Future of Expertise
Utpal Mangla (LI)
IBM, General Manager,
Industry EDGE Cloud;
IBM Cloud Platform

12. Emergent Expertise:
Finding and Creating
Knowledge for the Future
Heather Yurko (LI)
Mastercard, VP,
Digital Talent + Operations;
T-shaped leader
driving global outcomes
via technology, data +
culturally aligned strategies.

13. Knowledge Management/AI
and the Future of Expertise
Cindy Hubert (LI)
APQC, Executive Director,
American Productivity
and Quality Center

14. An NSF Perspective on
the Future of Expertise
Alexandra Medina-Borja (LI)
NSF, Program Director,
Engineering Cluster,
Division of
Undergraduate Education,
National Science Foundation

15. Panel 1: Q&A
Discussion

16. Break

17. Jim Spohrer (LI)
Retired Industry Executive,
and ISSIP event organizer
Future of Expertise
Panel 2: Introduction
1
2
3 4

18. Jim Spohrer (LI)
Retired Industry Executive,
and ISSIP event organizer
Future of Expertise
Panel 2: Introduction
Themes include but are not limited to:
Stakeholder perspectives on the importance of understanding the future of expertise
The practical challenges of hiring, on-boarding, engaging, and retaining top talent
AI/Digital Twins and the future of technology-enhanced expertise
Social networks, platforms, and future of influencer expertise
Democratizing the process of upskilling and gaining expertise
Risks and dangers, and how to responsibly build both better upskilling theory and practice

19. Analytics Thinking and
Adaptive Innovators
Haluk Demirkan (LI)
Amazon,
Head of Science for
Demand Forecasting,
Data Analytics &
Machine Learning

20. Industry Future Skills Needs:
A Research Perspective
Yassi Moghaddam (LI)
UC Santa Cruz – Silicon Valley,
Executive Director & Lecturer,
HCI Master Programs

21. Systems Savvy –
Thinking in 5T™
Terri Griffith (LI)
Simon Frasier University,
Keith Beedie Chair in
Innovation and Entrepreneurship,
Professor, Author
Abstract: Augmentation skills are a key dimension in the future of expertise.
How do we learn to think outside of ourselves such that we include powerful
automations as a matter of course?

22. Systems Savvy –
Thinking in 5T™
Terri Griffith (LI)
Simon Frasier University,
Keith Beedie Chair in
Innovation and Entrepreneurship,
Professor, Author

23. Tacit Knowledge
Management
Rodrigo Ribeiro (LI)
Professor of
Industrial Engineering
at the Federal University
of Minas Gerais (UFMG)
Abstract: Given that (i) experts are known for working better, faster and
safer than less experienced professionals and (ii) tacit knowledge is the
foundation of expertise, it follows that managing the tacit knowledge of
their employees is key for organizations’ competitiveness.

24. Tacit Knowledge
Management
Rodrigo Ribeiro (LI)
Professor of
Industrial Engineering
at the Federal University
of Minas Gerais (UFMG)

25. Panel 2: Q&A
Discussion

26. Jim Spohrer (LI)
Retired Industry Executive,
and ISSIP event organizer
Future of Expertise
Thank-you’s and Wrap Up

27. Backup Slides
• Questions from ISSIP Survey
• Some References

28. Questions
• “How do we help people understand what is expected of them as they enter new workforces (upskilling), and how they can
prepare? What role do broad-based digital knowledge standards play, for instance?” (S25)
• “What is next after AI and automation?” (S22)
• “Why are companies still hiring based on siloed discipline-based skills (e.g., programming skills; math skills; etc.) instead of the
adaptability and ability to learn of candidates?” (S21)
• “How might the concept and practices of developing technical expertise, in particular, differ culturally regarding the country and
your first language, and other countries and languages you know, whether this be the USA, or others? Thank you.” (S18)
• “How can I get you all to stop using the misleading term 'unlearning'? Not how our brain works.” (S17)
• “Is there more misinformation now than in the past? Or is it more obvious? I'm truly unsure of the answer and wonder how this
can be studied." (S9)
• "What other English words describe the notion of expertise?" (S6)
• “"How do you shift leaders who have built their style based on their own expertise to become more collaborative and inclusive of
other kinds of expertise in their solutioning?" (S2)
• "1. When do you think people will own a digital twin of themselves? 2. Besides service science, what other organizing frameworks
exist for T6 items (e.g., disciplines, systems, cultures, advancing technologies, work practices, and mindsets)?" (S1)

29. Some references

30. Trading Zones
”resolve the problem of incommensurability between
Kuhnian paradigms: how do scientists communicate
if paradigms are incommensurable?”
(Gallison 1997)
A General Model of Trading Zones
“A more general model of trading zones can be developed by
considering two dimensions along which trading zones can vary.
One dimension is the extent to which power is used to enforce
trade—this is the collaboration–coercion axis. The other
dimension is the extent to which trade leads to a
homogenous new culture—this is the
homogeneity– heterogeneity axis.”
(Collins, Evans, Gorman 2007)
Four ideal types – provide exemplars
Inter-language trading zone (high collaboration, high homogeneity)
Subversive trading zone (high coercion, high homogeneity)
Enforced trading zone (high coercion, high heterogeneity)
Fractionated trading zone (high collaboration, high heterogeneity)
“Another example of the use of interactional expertise
to create a trading zone is that of the San Francisco AIDS
activists described by Steven Epstein. The AIDS activists
mastered the language of medical research…”
“Yet another example is the field of gravitational
wave detection. This is a highly integrated esoteric science,
in which everyone is committed to the common goal
of building a gravitational wave detector that can detect the
twaves; there are perhaps 500 gravitational wave scientists.”

31. Expertise in Individuals, requiring deliberate practice
compared to novice performance on tasks like chess
(Chase and Simon 1973;
Elstein and Schwarz 2002;
Mylopoulos and Regehr 2007).
Individual expertise as a personal learning journey,
fluency reflected in less explicit deliberation
(Dreyfus 2004).
Expertise as social, relational/interactional, material
(Stevens et al. 2007;
Sanders and Harrison 2008;
Garrett et al. 2009;
Edwards 2010;
Kotzee 2012;
Fenwick and Nerland 2014;
Fenwick and Dahlgren 2015).
Expertise as translocal, economically invested, proprietary
(Nicolini et al 2018).
“the study of an innovative medical procedure called
transcatheter aortic valve implantation (TAVI). “
Competence - as learned and perpetuated by communities.
Expertise - as legitimated competence, therefore political.

32. “the automation of a ball mill”
Dreyfus – phenomenological perspective
Embodiment required to develop and maintain human expertise.
(Dreyfus 1979)
Collins – sociological perspective
Socialization (social embedding) into our form of life
required to develop and maintain human expertise.
(Collins 1996)
Synchronization
“Singular ability of the human body to “synchronize”
with the meaningful world of human practices and cultures”
(Merleau-Ponty, 2012 [1945])
Two types of actions/Two types of tacit knowledge
Mimeomorphic – content to carry out same way
Polimorphic – requires understanding of society
Somatic – bodies and brains of physical things
Collective – location in the social collectiveity
(Collins 1998; Collins 2007 )
Enhancement
“use of any artifact that makes the physical features of a perceptual
scene more perceptible for perceivers.” (Ribeiro 2017)
“My claim is that automation can replace some functions
of the human biological body, but it cannot replace its
phenomenal body—where human expertise lies.”
“Automation as displacement and facilitation”

33. Synchronization
“Synchronization refers to the process by which
perception becomes personalized. “
(Merleau-Ponty 2012 [1945] )
Pre-personal bodies and historical bodies.
“Synchronization turns pre-personal bodies into historical bodies.”
(Ribeiro 2014)
Competing forces
“perception is the outcome of three competing forces:
(a) the embodied experience of individuals,
(b) the physical features of the perceptual scene,
(c) the context.”
(Ribeiro 2014)
Sense
“Sense comes from our lived experience within social life and
practices and the physical world. It is because we are a natural
and living body that things matter to us, and sense can be born
and reborn while our body is shaped and reshaped. It is because
we are a historical body that events and objects may appear
similar or different to us.”
(Ribeiro 2014)
“…a US$3.2 billion industrial plant spread
in an area of 405 acres (164 hectares).
Built to produce 55,100 tons (50,000 tonnes)
of nickel per year … 1,500 people are necessary
to run the whole plant….” “Case 3—Seeing Relevance:
‘‘You look but you do not see’’ “

34. Tacit Knowledge
‘we can know more than we can tell’ (Polanyi (1983 [1966])
Explicit Knowledge
Can be articulated in formal languages. (Nonaka and Takeuchi 1995 )
Form of Life
Knowledge as the property of a social group (Wittgenstein 1976)
Scientific Paradigms
Result of social agreement (Kuhn 1996 [1962])
Worker Similarity
“qualify the experience of workers” (Ribeiro 2012)
Three Kinds of Judgements
“The capability of carrying out three kinds of judgement properly
and speedily is also put forward as being a core ability of those who
possess collective tacit knowledge.” (Ribeiro 2012)
- Similarity/difference
- Relevance/irrelevance
- Risk/opportunity
“The challenge dealt with and described here is
on how to professionally handle tacit knowledge
within organisations, and our case study is a
greenfield industrial plant in a very remote area
of Brazil.”