Presentation at a "Human Futures" and AI conference in Washington DC, April 2024

1. AI and the Futures of
Communities
Michael Madison
University of Pittsburgh
April 2024
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2. “Innovation”
Collective well-being
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3. Communities
Places, institutions, organizations, firms, market sectors,
disciplines, practices, identities, fields, groups, large and
small, formal and informal
Well-being
Health, education, happiness, wealth, opportunity,
capability, sustainability, resilience, purpose, both of the
community and of individuals exercising agency within it
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4. The question:
How does generative AI
(development, use) help or
hurt community well-
being?
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5. The response:
We don’t really know. Yet.
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6. Brief case study #1:
Future of work/future of
employment
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7. Will AI put people out of work?
Will AI change the nature of
employment (occupations)?
Will AI change the careers of workers?
Cf. Frey & Osborne, “The Future of
Employment” (2013)
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8. Ask about the community rather than
about the worker, or the firm, or the
occupation.
Ask the question about regional or local
employment patterns.
Consider: Pittsburgh.
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14. If Pittsburgh is:
(i) old and getting older,
(ii) smaller and getting smaller, and
(iii) seeing a re-distribution of employment patterns away
from “eds and meds” and toward “information,”
Then, as to employment, is development / use of generative AI:
(i) shifting the patterns in a more (productive) (equitable)
direction,
(ii) accelerating the patterns,
(iii) some of both (i) and (ii)
(iv) Neither
Is AI making Pittsburgh better or worse?
The analytic and policy challenge: the data does not exist at the
community level
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15. Briefer case study #2:
Academic research on the
character, uses, and
meanings of AI
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16. The problem:
The absence of an epistemic community that is
sufficiently and effectively broad and deep enough
to investigate
• shallow questions (what sorts of generative AI
models should we build?),
• intermediate questions (why/why not?), and
• foundational questions (how are we changing the
nature of knowledge and the nature of human
agency and sociability, and the character(s) of our
environment(s)?)
One community, or several?
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17. A solution?
Use the disruption introduced by ChatGPT to build new
community/ies – with respect to understanding AI, or with
respect to the nature of academic research generally, or both
– or observe the emergence of new epistemic communities
and communities of practice.
Example: University of Pittsburgh
• Top-down coordination: “Responsible Adoption of
Generative AI in Higher Education” (accepted for ACM
FAccT 2024 a/o 5 Apr ‘24)
• Bottom-up emergence: “PASTA”
Will this work?
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18. Briefest case studies:
AI systems and tools (“the smart city”) with respect to:
1. Misinformation/disinformation
2. Civic infrastructure
3. Public transit
4. Education
5. Human and family services
6. Air quality
7. Public health and health outcomes
8. Neighborhood equity
9. Public administration
10. … and more
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19. So what?
“Our” regulatory and policy toolbox is short on
strategies that aim at community-level, community-
specific interventions, that understand communities
as historically-rooted systems, and changeable, and
as parts of systems.
(“Self-regulation” “Norms”)
(Reasons.)
Do we have time to wait for a better toolbox to be
built?
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