I'm mainly arguing against public AI safety advocacy work, which was recently upvoted highly on the EA Forum.

I had the impression that it was more than just that, given the line: "In light of recent news, it is worth comprehensively re-evaluating which sub-problems of AI risk are likely to be solved without further intervention from the AI risk community (e.g. perhaps deceptive alignment), and which ones will require more attention." and the further attention devoted to deceptive alignment.

I appreciate these predictions, but I am not as interested in predicting personal of public opinions. I'm more interested in predicting regulatory stringency, quality, and scope. 

If you have any you think faithfully represent a possible disagreement between us go ahead. I personally feel it will be very hard to operationalize objective stuff about policies in a satisfying way. For example, a big issue with the market you've made is that it is about what will happen in the world, not what will happen without intervention from AI x-risk people. Furthermore it has all the usual issues with forecasting on complex things 12 years in advance, regarding the extent to which it operationalizes any disagreement well (I've bet yes on it, but think it's likely that evaluating and fixing deceptive alignment will remain mostly unsolved in 2035 conditional on no superintelligence, especially if there were no intervention from x-risk people).

I have three things to say here:

Thanks for clarifying.

Several months ago I proposed general, long-term value drift as a problem that I think will be hard to solve by default. I currently think that value drift is a "hard bit" of the problem that we do not appear to be close to seriously addressing, perhaps because people expect easier problems won't be solved either without heroic effort. I'm also sympathetic to Dan Hendrycks' arguments about AI evolution. I will add these points to the post.

Don't have a strong opinion here, but intuitively feels like it would be hard to find tractable angles for work on this now.

I mostly think people should think harder about what the hard parts of AI risk are in the first place. It would not be surprising if the "hard bits" will be things that we've barely thought about, or are hard to perceive as major problems, since their relative hiddenness would be a strong reason to believe that they will not be solved by default.

Maybe. In general, I'm excited about people who have the talent for it to think about previously neglected angles.

The problem of "make sure policies are well-targeted, informed by the best evidence, and mindful of social/political difficulties" seems like a hard problem that societies have frequently failed to get right historically, and the relative value of solving this problem seems to get higher as you become more optimistic about the technical problems being solved.

I agree this is important and it was in your post but it seems like a decent description of what the majority of AI x-risk governance people are already working on, or at least not obviously a bad one. This is the phrase that I was hoping would get made more concrete.

I want to emphasize that the current policies were crafted in an environment in which AI still has a tiny impact on the world. My expectation is that policies will get much stricter as AI becomes a larger part of our life. I am not making the claim that current policies are sufficient; instead I am making a claim about the trajectory, i.e. how well we should expect society to respond at a time, given the evidence and level of AI capabilities at that time.

I understand this (sorry if wasn't clear), but I think it's less obvious than you do that this trend will continue without intervention from AI x-risk people. I agree with other commenters that AI x-risk people should get a lot of the credit for the recent push. I also provided example reasons that the trend might not continue smoothly or even reverse in my point (3).

There might also be disagreements around:

1. Not sharing your high confidence in slow, continuous takeoff.
2. The strictness of regulation needed to make a dent in AI risk, e.g. if substantial international coordination is required it seems optimistic to me to assume that the trajectory will by default lead to this.
3. The value in things getting done faster than they would have done otherwise, even if they would have been done either way. This indirectly provides more time to iterate and get to better, more nuanced policy.

I believe that current evidence supports my interpretation of our general trajectory, but I'm happy to hear someone explain why they disagree and highlight concrete predictions that could serve to operationalize this disagreement.

Operationalizing disagreements well is hard and time-consuming especially when we're betting on "how things would go without intervention from a community that is intervening a lot", but a few very rough forecasts, all conditional on no TAI before resolve date:

1. 75%: In Jan 2028, less than 10% of Americans will consider AI the most important problem.
2. 60%: In Jan 2030, Evan Hubinger will believe that if x-risk-motivated people had not worked on deceptive alignment at all, risk from deceptive alignment would be at least 50% higher, compared to a baseline of no work at all (i.e. if risk is 5% and it would be 9% with no work from anyone, it needs to have been >7% if no work from x-risk people had been done to resolve yes).
3. 35%: In Jan 2028, conditional on a Republican President being elected in 2024, regulations on AI in the US will be generally less stringent than they were when the previous president left office. Edit: Crossed out because not operationalized well, more want to get at the vibe of how strict the President and legislature are being on AI, and since my understanding is a lot of the stuff from the EO might not come into actual force for a while.