Good observation. The only questions that don’t explicitly exclude it in the resolution criteria are “Will there be a massive catastrophe caused by AI before 2030?” and “Will an AI related disaster kill a million people or cause $1T of damage before 2070?”, but I think the question creators mean a catastrophic event that is more directly caused by the AI, rather than just a reaction to AI being released.
Manifold questions are sometimes somewhat subjective in nature, which is a bit problematic.
Alvin Ånestrand
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I think my points argue more that control research might have higher expected value than some other approaches, that don’t address delegation at all or are much less tractable. But I agree, if slop is the major problem, then most current control research doesn’t adress it, though it’s nice to see that this might change if Buck is right.
And my point about formal verification was to work around the slop problem by verifying the safety approach to a high degree of certainty. I don’t know if it’s feasible, though, but some seem to think so. Why do you think it’s a bad idea?
I can think of a few reasons someone might think AI Control research should receive very high priority, apart from what is mentioned in the post or in Buck’s comment:
You hope/expect early transformative AI to be used for provable safety approaches, using formal verification methods.
You think AI control research is more tractable than other research agendas, or will have useful results faster, before they are too late to apply.
Our only chance of aligning a superintelligence is to delegate the problem to AIs, either because it is too hard for humans, or it will arrive sooner than the proper alignment techniques can feasibly be developed.
You expect a significant fraction of total AI safety research over all time to be done by early transformative AI, so control research has high leverage value in improving the probability of successfully getting the AI to do valuable safety research, even if slop is quite likely.
I agree with basically everything in the post but put enough probability on these points to think that control research has really high expected value anyway.
The Alignment Mapping Program: Forging Independent Thinkers in AI Safety—A Pilot Retrospective
Interesting!
I thought of a couple of things that I was wondering if you have considered.
It seems to me like when examining mutual information between two objects, there might be a lot of mutual information that an agent cannot use. Like there is a lot of mutual information between my present self and me in 10 minutes, but most of that is in information about myself that I am not aware of, that I cannot use for decision making.
Also, if you examine an object that is fairly constant, would you not get high mutual information for the object at different times, even though it is not very agentic? Can you differentiate autonomy and a stable object?
I think my default response when I learn about [trait X] is almost the opposite of how it is described in the post, at least if I learn that someone I know has it.
My mind reflexively tries to explain how [trait X] is not that bad, or good in the certain context. I have had to force myself to not automatically defend it in my head. I might signal (consciously or unconsciously) dislike for the trait in general, but not when I am confronted with someone I know having it. There are probably exceptions to this though, maybe for more extreme traits. I hope I wouldn’t automatically try do internally defend rape for example, even if it was reflexive and only for one or two seconds.
I just wanted to note that people like me exist too, and in certain cultures it might be fairly common (though I’m just speculating here).
My apologies, when I started on the post I searched for the word “memorization”, and there were not many results. I forgot to change the statement when I realised there were more posts than I first thought.
Although, I still think there is too little discussion about memorization, perhaps with the exception of spaced repetition.
Thank you for pointing out the error.
Happy Amazing Breakthrough Day!