A research seminar to study public AI and other forms of public interest AI.

Season 3

Season 3 will start on April 22, 2025. We will survey diverse positions on AI emerging from art, culture, and the creative industries. In particular, we will consider the relationship between AI and the creative industries through four lenses: political power, cultural power, technological power, and economic power. Several spots will be reserved for creative professionals in any medium interested in exploring public AI. If you are interested in joining the seminar, please apply here by April 15, 2025.

  • (Optional) April 21: Introductions & goals of the seminar
  • April 22: Do Not Train, with Mat Dryhurst (artist), and AI and copyright, with Reema Selhi (DACS, British Copyright Council) - Video, Summary
  • April 29: Generative AI is not useful for making art, with Ted Chiang (author)
  • May 6: Community data and the case of Common Voice, with EM Lewis-Jong (Mozilla) - Summary
  • May 13: A Vision for Public AI in California, with Teri Olle and Taylor Jo Isenberg (Economic Security Project) - Video, Summary
  • May 20: Public interest AI, with Martin Tisné (AI Collaborative, Current AI) - Video, Summary
  • May 27: AI & entertainment industry, with David White (3CG Ventures), and AI & the freelancer economy, with Angie Kim and Jessica Mele (CCI) - Video, Summary
  • June 3: Past and future narratives for tech, with Gideon Lichfield (journalist) and Nils Gilman (historian) - Video, Summary
  • June 10: The near possible future of AI, with Kim Stanley Robinson (author) - Video, Summary
  • (Special Session) July 11: The National Deep Inference Fabric, with David Bau (Northeastern) - Video, Summary

Organizers: Joshua Tan (Metagov), Alek Tarkowski (Open Future), B Cavello (Aspen Digital)

Season 2

Season 2 will start on August 13, 2024 and conclude on October 15, 2024. We will focus especially on connecting and relating a cluster of political narratives around public AI, including responsible/safe AI, public compute, sovereign/national AI, democratic AI, open source AI, and AI for science. If you are interested in joining the seminar, please apply here by July 31, 2024.

  • (Optional) August 6: Introductions & goals of the seminar
  • August 13: Towards a network of publicly-funded AI labs, with Yoshua Bengio (MILA) - Video, Summary
  • August 20: Public compute, with Nicole DeCario (Allen Institute) and Katie Antypas (National Science Foundation) - Video, Summary
  • August 27: SEA-LION, with Leslie Teo (AI Singapore) - Video, Summary
  • September 3: AI and the labor market, with Julia Lane (NYU) and Adam Leonard (Texas Workforce Commission) - Video, Summary
  • September 10: The role of openness in AI, with Irene Solaiman (HuggingFace) - Video, Summary
  • September 17: Democratic AI, with Divya Siddarth (Collective Intelligence Project) - Video, Summary
  • September 24: GPT-SW3, with Magnus Sahlgren (AI Sweden) - Video, Summary
  • October 1: Community power in AI, with Jeni Tennison (Connected by Data) - Video, Summary
  • October 8: The AI Dilemma, with Aza Raskin (Center for Humane Technology) - Video, Summary
  • October 15: AI Nationalisms, with Sarah Myers West and Amba Kak (AI Now) - Video, Summary

Organizers: Joshua Tan (Oxford, Metagov), Alex Krasodomski (Chatham House), B Cavello (Aspen Digital)

Season 1

  • January 9: Public options for AI, with Bruce Schneier (Harvard) - Video, Summary
  • January 16: Public policy for tech, with Diane Coyle (Cambridge) - Video, Summary
  • January 23: Case study: AuroraGPT & BritGPT, with Rick Stevens (Chicago / Argonne National Labs) and Hannah O’Rourke (Labour Longterm) - Video, Summary
  • January 30: Break
  • February 6: The politics of AI, with Julia Angwin (New York Times / Harvard) - Video, Summary
  • February 13: Industrial organization and antimonopoly, with Ganesh Sitaraman (Vanderbilt) - Video, Summary
  • February 20: Lessons from digital public infrastructure, with David Eaves (UCL) - Video, Summary
  • February 27: AI and democracy, with Lawrence Lessig (Harvard) - Video, Summary
  • March 5: Synthesis

Over the course of the seminar, we will consider different models of public AI, lessons from both history and from AI, general theories of public investment and of regulation, as well as many different arguments for and against public AI. Four themes will guide our considerations: public benefit, public accountability, market failure, and political narratives.

Organizers: Joshua Tan (Oxford, Metagov), SJ Klein (Berkman, Interlace), Nick Garcia (Public Knowledge)

Details

  • Format: the seminar is invite-only. The first half of the seminar, reserved for invited talks, is recorded via Zoom and posted online. Notes from the entire seminar will be summarized without named attribution under the Chatham House rule.
  • Meeting times: every Tuesday from 11am - 1pm ET over Zoom.
  • Recordings and notes will be posted online at https://publicai.network/seminar.

Goals

The Public AI Seminar has two parallel objectives:

  • To develop a body of research, ideas, and tools to support the development of public AI and other forms of public interest AI.
  • To foster an intellectual community capable of describing, guiding, and implementing public AI and other forms of public interest AI.