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.
Ok, so some societies have much higher murder rates than others. Some locations, the local police de facto make murder between gang members legal, by accepting low bribes and putting minimal effort into investigation.
The issue is runaway differential utility. The few examples of human technology not exploited do not have runaway utility. They have small payoffs delayed far into the future and large costs, and making even a small mistake makes the payoff negative.
Examples : genetic engineering, human medicine, nuclear power. Small payoffs and it's negative on the smallest error.
AI is different. It appears to have immediate more than 100 percent annual payoff. OpenAIs revenue on a model they state cost 68 million to train is about 1 billion USD a month. Assuming 10 percent profit margin (the rest pays for compute) that's over 100 percent annual ROI.
So a society that has less moral disgust towards AI would get richer. They spend their profits on buying more AI hardware and more research. Over time they own a larger and larger fraction of all assets and revenue on earth. This is why EMH forces companies towards optimal strategies, because over time the ones that fail to do so fail financially. (they fail when their cost of production becomes greater than the market price for a product. Example: Sear. Sears failed to modernize its logistics chain so eventually it's cost to deliver retail goods exceeds the market price for those goods).
Moreover, other societies, forced to compete, have to drop some of their moral disgust and I suspect this scenario ends up like a ratchet, where inevitably a society will lose 100 percent of all disgust in order to compete.
Pauses, multilateral agreements, etc can slow this down but it depends on how fast the gain is as to how long it buys you. Unilateral agreements just free tsmc up to manufacture AI chips for the parties not signing the agreement.