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The National Academies of Science, Engineering, and Mathematics are hosting a virtual workshop on the topic of “AI to Assist Mathematical Reasoning” from June 12-14. The tentative program can be found here. I am one of the members of the organizing committee for this workshop, together with Petros Koumoutsakos, Jordan Ellenberg, Melvin Greer, Brendan Hassett, Yann A. LeCun, Heather Macbeth, Talia Ringer, Kavitha Srinivas, and Michelle Schwalbe. There is some thematic overlap (and a few speakers in common) with the recent IPAM program on machine assisted proof, though with more of a focus on the current and projected technical capabilities of machine learning algorithms for mathematics. Registration for the event is currently open at the web page for the workshop.

As part of my duties on the Presidential Council of Advisors on Science and Technology (PCAST), I am co-chairing (with Laura Greene) a working group studying the impacts of generative artificial intelligence technology (which includes popular text-based large language models such as ChatGPT or diffusion model image generators such as DALL-E 2 or Midjourney, as well as models for scientific applications such as protein design or weather prediction), both in science and in society more broadly. To this end, we will have public sessions on these topics during our PCAST meeting next week on Friday, May 19, with presentations by the following speakers, followed by an extensive Q&A session:

The event will be livestreamed on the PCAST meeting page. I am personally very much looking forward to these sessions, as I believe they will be of broad public interest.

In parallel to this, our working group is also soliciting public input for submissions from the public on how to identify and promote the beneficial deployment of generative AI, and on how best to mitigate risks. Our initial focus is on the challenging topic of how to detect, counteract, and mitigate AI-generated disinformation and “deepfakes”, without sacrificing the freedom of speech and public engagement with elected officials that is needed for a healthy democracy to function; in the future we may also issue further requests centered around other aspects of generative AI. Further details of our request, and how to prepare a submission, can be found at this link.

We also encourage submissions to some additional requests for input on AI-related topics by other agencies:

  1. The Office of Science Technology and Policy (OSTP) Request for Information on how automated tools are being used to surveil, monitor, and manage workers.
  2. The National Telecommunications and Information Administration (NTIA) request for comment on AI accountability policy.

Readers who wish to know more about existing or ongoing federal AI policy efforts may also be interested in the following resources:

  • The White House Blueprint for an AI Bill of Rights lays out core aspirational principles to guide the responsible design and deployment of AI technologies.
  • The National Institute of Standards and Technology (NIST) released the AI Risk Management Framework to help organizations and individuals characterize and manage the potential risks of AI technologies.
  • Congress created the National Security Commission on AI, which studied opportunities and risks ahead and the importance of guiding the development of AI in accordance with American values around democracy and civil liberties.
  • The National Artificial Intelligence Initiative was launched to ensure U.S. leadership in the responsible development and deployment of trustworthy AI and support coordination of U.S. research, development, and demonstration of AI technologies across the Federal government.
  • In January 2023, the Congressionally mandated National AI Research Resource (NAIRR) Task Force released an implementation plan for providing computational, data, testbed, and software resources to AI researchers affiliated with U.S organizations.