Public AI Seminar

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

Season 2

Season 2 will run through August and September, starting on August 13, 2024 and concluding on October 8. The final schedule will be posted in early August.

For the fall of 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 25, 2024.

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‚ÄôRourke (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

Details

  • Organizers: Joshua Tan (Oxford, Metagov), Alex Krasodomski (Chatham House), B Cavello (Aspen Digital)
  • 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.
  • Previous organizers: SJ Klein (Berkman, Interlace), Nick Garcia (Public Knowledge).

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.

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.