MaximeCdS

Solving the moral cluelessness problem with Bayesian joint probability distributions

Hey!

I think Hilary Greaves does a great job at explaining what cluelessness in non-jargon terms in her most recent appearance on 80K podcast.

As far as I understand it, cluelessness arises because, as we don't have sufficient evidence, we're very unsure about what our credence should be, to the point they feel -or maybe just *are- *arbitrary. In this case, you could still just carry out the expected value calculation and opt to do the most choice worthy action as you suggest. However, it seems unsatisfying because the credence function you use is arbitrary. Indeed, given your level of evidence, you could very well have opted for another set of beliefs that would have lead you to act differently.

Thus, one might argue that in order to be rational in this type of predicament, you have to consider several probability functions that are consistent with the evidence you have. In other words, you are required to have "imprecise credences" because you cannot determine in a principled manner which probability function you should use.

As Hilary Greaves herself points out in the podcast I mentioned above, if you're not troubled by this, and you're by yourself, you can just compute the expected value, but issues can arise when you try to coordinate with other agents that have different arbitrary beliefs. This is why it might be important to take cluelessness seriously.

I hope this helps!

I'm not sure what makes you think that. Prof. Greaves does state that rational agents may be required "to include all such equally-recommended credence functions in their representor". This feels a lot less arbitrary that deciding to pick a

single prioramong all those available and decide to compute the expected value of your actions based on it.I agree that you could do that, but it seems even more arbitrary! If you think that choosing a set of probability functions was arbitrary, then having a

meta-probability distributionover your probability distributions seems even more arbitrary, unless I'm missing something. It doesn't seem to me like the kind of situations where going meta helps: intuitively, if someone is very unsure about what prior to use in the first place, they should also probably be unsure about coming up with a second-order probability distribution over their set of priors .I do not think that's what Prof. Greaves mean when she says "imprecise credence". This article for the Stanford Encyclopedia of Philosophy explains the meaning of that phrase for philosophers. It also explains what a representor is in a better way that I did.

I think Prof. Greaves and Philip Trammel would disagree with that, which is why they're talking about cluelessness. For instance, Phil writes:

Hope this helps.