I would say they can be reduced to numbers like that today, it's just that the implied error bars around the numbers would be huge. Then in the optimization pr

I would say they can be reduced to numbers like that today, it's just that the implied error bars around the numbers would be huge. Then in the optimization problem of determining what to invest donations into, the amount of gain from putting money into AI research would be correspondingly penalized by the amount of uncertainty (this is known as mean-variance optimization). It's very much like a choice to invest in a solid, fundamental company which you know will give you 5% return next quarter, or invest in a very uncertain start-up which might give you 1000% return next quarter or might give you -50%. The start-up investment might have a higher expected value, but also a much higher risk. At that point, the way to distinguish between whether you prefer to invest in the "sure bet" company or the "risky and ambiguous" start-up would be down to your personal tolerance for risk. It could be perfectly rational to invest in the start-up in that situation. If you personally have a high risk tolerance. If you don't, then the start-up would look like a crazy, speculative bet with huge downside. So some people might look at AI and say, "We don't have a good idea what the capabilities will be in ~50 years. So there is a huge risk that my charity donations will be wasted because in 50 years we realize we never needed to worry about this problem. Or we might use current AI research to thwart an unimaginable global crisis." That person then looks into various sources of thought on putting actual numbers and actual error bars, the best we can, onto the problem, say by reading the Global Catastrophic Risk book, or stuff by Bostrom, or consulting surveys of current practitioners' estimates. At the end of that process, it could totally end up being the rational course of action for that person to still invest in AI charities. Yes, their estimate for the expected value of the donation might have huge error bars around it, but under their particular beliefs about risk-return trade-offs, that might not cause their optimized decision to change.