(There was a LaTeX error in my comment, which made it totally illegible. But I think you managed to resolve my confusion anyway).

I see! It's not provable that Provable() implies . It seems like it should be provable, but the obvious argument relies on the assumption that, if * is provable, then it's not also provable that - in other words, that the proof system is consistent! Which may be true, but is not provable.

The asymmetry between 5 and 10 is that, to choose 5, we only need a proof that 5 is optimal, but to choose 10, we need to not find a proof that 5 is optimal. Which seems easier than finding a proof that 10 is optimal, but is not provably easier.

Decision Theory

by abramdemski, Scott Garrabrant 1 min read31st Oct 201837 comments

101

Ω 24


Crossposted from the AI Alignment Forum. May contain more technical jargon than usual.

(A longer text-based version of this post is also available on MIRI's blog here, and the bibliography for the whole sequence can be found here.)

The next post in this sequence, 'Embedded Agency', will come out on Friday, November 2nd.

Tomorrow’s AI Alignment Forum sequences post will be 'What is Ambitious Value Learning?' in the sequence 'Value Learning'.