I don’t have a nice clean citation. I don’t think one exists. I’ve looked at an awful lot of individual opinions and different surveys. I guess the biggest reason I’m convinced this correlation exists is that arguments for low p(doom) very rarely actually engage arguments for risk at their strong points (when they do the discussions are inconclusive in both directions—I’m not arguing that alignment is hard, but that it’s very much unknown how hard it is).
There appears to be a very high correlation between misunderstanding the state of play, and optimism. And because it’s a very complex state of arguments, the vast majority of the world misunderstands it pretty severely.
I very much wish it was otherwise; I am an optimist who has become steadily more pessimistic as I’ve made alignment my full-time focus—because the arguments against are subtle (and often poorly communicated) but strong.
They arguments for the difficulty of alignment are far too strong to be rationally dismissed down to the 1.4% or whatever it was that the superforecasters arrived at. They have very clearly missed some important points of argument.
The anticorrelation with academic success seems quite right and utterly irrelevant. As a career academic, I have been noticing for decades that academic success has some quite perverse incentives.
I agree that there are bad arguments for pessimism as well as optimism. The use of bad logic in some prominent arguments says nothing about the strength of other arguments. Arguments on both sides are far from conclusive. So you can hope arguments for the fundamental difficulty of aligning network-based AGI are wrong, but assigning a high probability they’re wrong without understanding them in detail and constructing valid counterarguments is tempting but not rational.
If there’s a counterargument you find convincing, please point me to it! Because while I’m arguing from the outside view, my real argument is that this is an issue that is unique in intellectual history, so it can really only be evaluated from the inside view. So that’s where most of my thoughts on the matter go.
All of which isn’t to say the doomers are right and we’re doomed if we don’t stop building network-based AGI. I’m saying we don’t know. I’m arguing that assigning a high probability right now based on limited knowledge to humanity accomplishing alignment is not rationally justified.
I think that fact is reflected in the correlation of p(doom) with time-on-task only on alignment specifically. If that’s wrong I’d be shocked, because it looks very strong to me, and I do work hard to correct for my own biases. But it’s possible I’m wrong about this correlation. If so it will make my day and perhaps my month or year!
It is ultimately a question that needs to be resolved at the object level; we just need to take guesses about how to assign resources based on outside views.
I think the critical crux here is the assumption about human competence, individually and working in groups. And I’m afraid I agree; humans have an optimism bias by many measures. Our track record on doing even easy projects right on the first try (or even the first few tries) is not good.
I also think optimists are often asking the question could we solve alignment, while pessimists are asking will we solve alignment, which includes a lot more practical difficulties so more opportunities for failure.
Of course there are many other relevant cruxes, but I think those two are pretty common and the first is the biggest contribution of this particular contribution.