there are multiple possible ways to interpret the final environment in the paper in terms of the analogy to the future:
As the catastrophic failure that results from reward hacking. In this case, we might care about frequency depending on the number of opportunities the model would have and the importance of collusion.
You’re correct that I was neglecting this threat model—good point, and thanks.
So, given this overall uncertainty, it seems like we should have a much fuzzier update where higher numbers should actually update us.
Hmm, here’s another way to frame this discussion:
Sam: Before evaluating the RTFs in the paper, you should apply a ~sigmoid function with the transition region centered on ~10^-6 or something. Note that all of the RTFs we’re discussing come after this transition.
Ryan: While it’s true that we should first be applying a ~sigmoid, we should have uncertainty over where the transition region begins. When taking this uncertainty into account, the way to decide importance boils down to comparing the observed RTF to your distribution of thresholds in a way which is pretty similar to what people were implicitly doing anyway.
Does that sound like a reasonable summary? If so, I think I basically agree with you.
(I do think that it’s important to keep in mind that for threat models where reward hacking is reinforced, small RTFs might matter a lot, but maybe that was already obvious to everyone.)
I do think that it’s important to keep in mind that for threat models where reward hacking is reinforced, small RTFs might matter a lot, but maybe that was already obvious to everyone.
I don’t think this was obvious to everyone and I appreciate this point—I edited my earlier comment to more explicitly note my agreement.
You’re correct that I was neglecting this threat model—good point, and thanks.
Hmm, here’s another way to frame this discussion:
Sam: Before evaluating the RTFs in the paper, you should apply a ~sigmoid function with the transition region centered on ~10^-6 or something. Note that all of the RTFs we’re discussing come after this transition.
Ryan: While it’s true that we should first be applying a ~sigmoid, we should have uncertainty over where the transition region begins. When taking this uncertainty into account, the way to decide importance boils down to comparing the observed RTF to your distribution of thresholds in a way which is pretty similar to what people were implicitly doing anyway.
Does that sound like a reasonable summary? If so, I think I basically agree with you.
(I do think that it’s important to keep in mind that for threat models where reward hacking is reinforced, small RTFs might matter a lot, but maybe that was already obvious to everyone.)
Yep, reasonable summary.
I don’t think this was obvious to everyone and I appreciate this point—I edited my earlier comment to more explicitly note my agreement.