FHI has released a new tech report:
Armstrong, Bostrom, and Shulman. Racing to the Precipice: a Model of Artificial Intelligence Development.
Abstract:
This paper presents a simple model of an AI arms race, where several development teams race to build the first AI. Under the assumption that the first AI will be very powerful and transformative, each team is incentivized to finish first — by skimping on safety precautions if need be. This paper presents the Nash equilibrium of this process, where each team takes the correct amount of safety precautions in the arms race. Having extra development teams and extra enmity between teams can increase the danger of an AI-disaster, especially if risk taking is more important than skill in developing the AI. Surprisingly, information also increases the risks: the more teams know about each others’ capabilities (and about their own), the more the danger increases.
The paper is short and readable; discuss it here!
But my main reason for posting is to ask this question: What is the most similar work that you know of? I'd expect people to do this kind of thing for modeling nuclear security risks, and maybe other things, but I don't happen to know of other analyses like this.
Aha. That is the reason they failed with Skynet.
OK. Joke aside. From the paper (it is really short) I see that for the safest case (two teams none aware of the other or of their capability and their capability is higher than their enmity) the risk is 0. But this is due to a simplification and only a first order approximation.
Given that we might structure AI development such that AI research must be registered and no communication not thru the AI authority is allowed (OK, that might be circumvented but at least reduces risk) then we may arrive at the zero case above.
But it is not really zero. I'm interested in the exact value as that might still be too high.
Note that I think that the capability e will most likely exceed the enmity $\mu$ because the risk of AI failure is so high.