In March of this year, 30,000 people, including leading AI figures like Yoshua Bengio and Stuart Russell, signed a letter calling on AI labs to pause the training of AI systems. While it seems unlikely that this letter will succeed in pausing the development of AI, it did draw substantial attention to slowing AI as a strategy for reducing existential risk.
While initial work has been done on this topic (this sequence links to some relevant work), many areas of uncertainty remain. I’ve asked a group of participants to discuss and debate various aspects of the value of advocating for a pause on the development of AI on the EA Forum, in a format loosely inspired by Cato Unbound.
- On September 16, we will launch with three posts:
- David Manheim will share a post giving an overview of what a pause would include, how a pause would work, and some possible concrete steps forward
- Nora Belrose will post outlining some of the risks of a pause
- Thomas Larsen will post a concrete policy proposal
- After this, we will release one post per day, each from a different author
- Many of the participants will also be commenting on each other’s work
Responses from Forum users are encouraged; you can share your own posts on this topic or comment on the posts from participants. You’ll be able to find the posts by looking at this tag (remember that you can subscribe to tags to be notified of new posts).
I think it is unlikely that this debate will result in a consensus agreement, but I hope that it will clarify the space of policy options, why those options may be beneficial or harmful, and what future work is needed.
People who have agreed to participate
These are in random order, and they’re participating as individuals, not representing any institution:
- David Manheim (ALTER)
- Matthew Barnett (Epoch AI)
- Zach Stein-Perlman (AI Impacts)
- Holly Elmore (AI pause advocate)
- Buck Shlegeris (Redwood Research)
- Anonymous researcher (Major AI lab)
- Anonymous professor (Anonymous University)
- Rob Bensinger (Machine Intelligence Research Institute)
- Nora Belrose (EleutherAI)
- Thomas Larsen (Center for AI Policy)
- Quintin Pope (Oregon State University)
Scott Alexander will be writing a summary/conclusion of the debate at the end.
Thanks to Lizka Vaintrob, JP Addison, and Jessica McCurdy for help organizing this, and Lizka (+ Midjourney) for the picture.
PSA: the term "compute overhang" or "hardware overhang" has been used in many ways. Today it seems to most often (but far from always) mean amount labs can quickly scale up the size of the largest training run (especially because a ban on large training runs ends). When you see it or use it, make sure everyone knows what it means.
(It will come up often in this debate.)
Relatedly, there's something like a soft pause or slowdown where you slow training runs using compute beyond a certain threshold, but the threshold is moving every year. This could be a pragmatic tweak because compute will likely get cheaper, so it becomes easier for rogue actors to circumvent the compute cap if it never moves. This soft pause idea has been referred to as "moving bright line (of a compute cap)."