A list of good heuristics that the case for AI X-risk fails

As a meta-comment, I think it's quite unhelpful that some of these "good heuristics" are written as intentional strawmen where the author doesn't believe the assumptions hold. E.g., the author doesn't believe that there are no insiders talking about X-risk. If you're going to write a post about good heuristics, maybe try to make the good heuristic arguments actually good? This kind of post mostly just alienates me from wanting to engage in these discussions, which is a problem given that I'm one of the more senior AGI safety researchers.

Phil Trammell makes a similar point about how we should update from the fact that smart people refuse to engage with AI risk arguments:

" The upshot here seems to be that when a lot of people disagree with the experts on some issue, one should often give a lot of weight to the popular disagreement, even when one is among the experts and the people's objections sound insane. Epistemic humility can demand more than deference in the face of peer disagreement: it can demand deference in the face of disagreement from one's epistemic inferiors, as long as they're numerous. They haven't engaged with the arguments, but there is information to be extracted from the very fact that they haven't bothered engaging with them. "

I'd second the suggestion of checking out the comments.

There are also a few extra comments on the LessWrong version of the post, which aren't on the Alignment Forum version.

Here's the long-winded comment I made there:

I think this list is interesting and potentially useful, and I think I'm glad you put it together. I also generally think it's a good and useful norm for people to seriously engage with the arguments they (at least sort-of/overall) disagree with.

But I'm also a bit concerned about how this is currently presented. In particular:

• This is titled "A list of good heuristics that the case for AI x-risk fails".
• The heuristics themselves are stated as facts, not as something like "People may believe that..." or "Some claim that..." (using words like "might" could also help).
• A comment of yours suggests you've already noticed this. But I think it'd be pretty quick to fix.
• Your final paragraph, a very useful caveat, comes after listing all the heuristics as facts.

I think these things will have relatively small downsides, given the likely quite informed and attentive audience here. But a bunch of psychological research I read a while ago (2015-2017) suggests there could be some degree of downsides. E.g.:

Information that initially is presumed to be correct, but that is later retracted or corrected, often continues to influence memory and reasoning. This occurs even if the retraction itself is well remembered. The present study investigated whether the continued influence of misinformation can be reduced by explicitly warning people at the outset that they may be misled. A specific warning--giving detailed information about the continued influence effect (CIE)--succeeded in reducing the continued reliance on outdated information but did not eliminate it. A more general warning--reminding people that facts are not always properly checked before information is disseminated--was even less effective. In an additional experiment, a specific warning was combined with the provision of a plausible alternative explanation for the retracted information. This combined manipulation further reduced the CIE but still failed to eliminate it altogether.

And also:

Information presented in news articles can be misleading without being blatantly false. Experiment 1 examined the effects of misleading headlines that emphasize secondary content rather than the article’s primary gist. [...] We demonstrate that misleading headlines affect readers’ memory, their inferential reasoning and behavioral intentions, as well as the impressions people form of faces. On a theoretical level, we argue that these effects arise not only because headlines constrain further information processing, biasing readers toward a specific interpretation, but also because readers struggle to update their memory in order to correct initial misconceptions.

Based on that sort of research (for a tad more info on it, see here), I'd suggest:

• Renaming this to something like "A list of heuristics that suggest the case for AI x-risk is weak" (or even "fails", if you've said something like "suggest" or "might")
• Rephrasing the heuristics to stated as disputable (or even false) claims, rather than facts. E.g., "Some people may believe that this concern is being voiced exclusively by non-experts like Elon Musk, Steven Hawking, and the talkative crazy guy next to you on the bus." ETA: Putting them in quote marks might be another option for that.
• Moving what's currently the final paragraph caveat to before the list of heuristics.
• Perhaps also adding sub-points about the particularly disputable dot points. E.g.:
• "(But note that several AI experts have now voiced concern about the possibility of major catastrophes from advanced AI system, although there's still not consensus on this.)"

I also recognise that several of the heuristics really do seem good, and probably should make us at least somewhat less concerned about AI. So I'm not suggesting trying to make the heuristics all sound deeply flawed. I'm just suggesting perhaps being more careful not to end up with some readers' brains, on some level, automatically processing all of these heuristics as definite truths that definitely suggest AI x-risk isn't worth of attention.

Sorry for the very unsolicited advice! It's just that preventing gradual slides into false beliefs (including from well-intentioned efforts that do actually contain the truth in them!) is sort of a hobby-horse of mine.

[And then I replied to myself with the following]

Also, one other heuristic/proposition that, as far as I'm aware, is simply factually incorrect (rather than "flawed but in debatable ways" or "actually pretty sound") is "AI researchers didn't come up with this concern, Hollywood did. Science fiction is constructed based on entertaining premises, not realistic capabilities of technologies." So there it may also be worth pointing out in some manner that, in reality, quite early on prominent AI researchers raised concerns somewhat similar to those discussed now.

E.g., I. J. Good apparently wrote in 1959:

Whether [an intelligence explosion] will lead to a Utopia or to the extermination of the human race will depend on how the problem is handled by the machines. The important thing will be to give them the aim of serving human beings.

I'm not sure whether this counts as a heuristic or not, but anyway... I think an important point is that it's not clear what the incentive problem is, or (more weakly) that the incentive problem is nowhere near as bad as suggested in classical AI risk arguments. Designers of AI systems have very strong incentives for them not to be as useless as painted in classical AI risk arguments. If you were running a paperclip company, you would very strongly want to figure out a way to make a paperclip maximiser that doesn't use people's atoms to make paperclips, and there would be lots of opportunities to learn as you go on this front - there would be incentives for capabilities to develop in tow with safety

The incentive problem is made better by the fact that the market for AI development is quite concentrated - there are <10 major players in the field who currently look most likely to make very advanced AGIs. Thus, you only need to get coordination on safety from <10 actors. In contrast, biotechnology is comparatively a complete nightmare from a coordination point of view, requiring coordination among pretty much all states. Climate change also seems difficult on this front, though less bad than bio.