I think the idea that if one AI says there is a 50% chance of heads, and the other AI says there is a 90% chance of heads, the first AI can describe the second AI as knowing that there is a 50% chance, but caring more about the heads outcome. Since it can redescribe the other’s probabilities as matching its own, agreement on what should be done will be possible. None of this means that anyone actually decides that something will be worth more to them in the case of heads.
the first AI can describe the second AI as knowing that there is a 50% chance, but caring more about the heads outcome.
First of all this makes any sense solely in the decision-taking context (and not in the forecast-the-future context). So this is not about what will actually happen but about comparing the utilities of two outcomes. You can, indeed, rescale the utility involved in a simple case, but I suspect that once you get to interdependencies and non-linear consequences things will get more hairy, if possible at all.
Besides, this requires you to know the utility function in question.
I think the idea that if one AI says there is a 50% chance of heads, and the other AI says there is a 90% chance of heads, the first AI can describe the second AI as knowing that there is a 50% chance, but caring more about the heads outcome. Since it can redescribe the other’s probabilities as matching its own, agreement on what should be done will be possible. None of this means that anyone actually decides that something will be worth more to them in the case of heads.
First of all this makes any sense solely in the decision-taking context (and not in the forecast-the-future context). So this is not about what will actually happen but about comparing the utilities of two outcomes. You can, indeed, rescale the utility involved in a simple case, but I suspect that once you get to interdependencies and non-linear consequences things will get more hairy, if possible at all.
Besides, this requires you to know the utility function in question.