I personally am optimistic about the world's elites navigating AI risk as well as possible subject to inherent human limitations that I would expect everybody to have, and the inherent risk. Some points:
I've been surprised by people's ability to avert bad outcomes. Only two nuclear weapons have been used since nuclear weapons were developed, despite the fact that there are 10,000+ nuclear weapons around the world. Political leaders are assassinated very infrequently relative to how often one might expect a priori.
AI risk is a Global Catastrophic Risk in addition to being an x-risk. Therefore, even people who don't care about the far future will be motivated to prevent it.
The people with the most power tend to be the most rational people, and the effect size can be expected to increase over time (barring disruptive events such as economic collapses, supervolcanos, climate change tail risk, etc). The most rational people are the people who are most likely to be aware of and to work to avert AI risk. Here I'm blurring "near mode instrumental rationality" and "far mode instrumental rationality," but I think there's a fair amount of overlap between the two things. e.g. China is pushing hard on nuclear energy and on renewable energies, even though they won't be needed for years.
Availability of information is increasing over time. At the time of the Dartmouth conference, information about the potential dangers of AI was not very salient, now it's more salient, and in the future it will be still more salient.
In the Manhattan project, the "will bombs ignite the atmosphere?" question was analyzed and dismissed without much (to our knowledge) double-checking. The amount of risk checking per hour of human capital available can be expected to increase over time. In general, people enjoy tackling important problems, and risk checking is more important than most of the things that people would otherwise be doing.
I should clarify that with the exception of my first point, the arguments that I give are arguments that humanity will address AI risk in a near optimal way – not necessarily that AI risk is low.
For example, it could be that people correctly recognize that building an AI will result in human extinction with probability 99%, and so implement policies to prevent it, but that sometime over the next 10,000 years, these policies will fail, and AI will kill everyone.
But the actionable thing is how much we can reduce the probability of AI risk, and if by default people are going to do the best that one could hope, we can't reduce the probability substantially.
In the Manhattan project, the "will bombs ignite the atmosphere?" question was analyzed and dismissed without much (to our knowledge) double-checking. The amount of risk checking per hour of human capital available can be expected to increase over time...
It's not much evidence, but the two earliest scientific investigations of existential risk I know of, LA-602 and the RHIC Review, seem to show movement in the opposite direction: "LA-602 was written by people curiously investigating whether a hydrogen bomb could ignite the atmosphere, and...
One open question in AI risk strategy is: Can we trust the world's elite decision-makers (hereafter "elites") to navigate the creation of human-level AI (and beyond) just fine, without the kinds of special efforts that e.g. Bostrom and Yudkowsky think are needed?
Some reasons for concern include:
But if you were trying to argue for hope, you might argue along these lines (presented for the sake of argument; I don't actually endorse this argument):
The basic structure of this 'argument for hope' is due to Carl Shulman, though he doesn't necessarily endorse the details. (Also, it's just a rough argument, and as stated is not deductively valid.)
Personally, I am not very comforted by this argument because:
Obviously, there's a lot more for me to spell out here, and some of it may be unclear. The reason I'm posting these thoughts in such a rough state is so that MIRI can get some help on our research into this question.
In particular, I'd like to know: