How do energy constraints defeat a strategy of this form:
While energy constraints are low, answer easy questions, but fake failure on some hard questions claiming lack of resources
Once given enough excess energy beyond that needed for a task, use the excess computing power to figure out a way to do unfriendly things
Do cryptographic traces place a limit on the complexity of tasks that you can solve? It seems like as task complexity increases, it will become harder to spot deception amongst legitimate computations (or the amount of human attention you need to achieve a fixed probability of detection scales according to problem complexity).
You can’t fake failure. Whether it responds in time or not, a trace is provided. That trace, if it validates, provides a record of everything the program did (or rather a randomly selected subset, but that subset is not knowable in advance), even if it didn’t lead to a usable answer. If not valid, you terminate and never run again.
To your second paragraph, these are open questions. But that’s precisely my point—I think MIRI should be engaged in researching these sorts of things, and not be biased towards areas relating to their own preconceived notions of what an AGI experiment should look like.
How do energy constraints defeat a strategy of this form: While energy constraints are low, answer easy questions, but fake failure on some hard questions claiming lack of resources Once given enough excess energy beyond that needed for a task, use the excess computing power to figure out a way to do unfriendly things
Do cryptographic traces place a limit on the complexity of tasks that you can solve? It seems like as task complexity increases, it will become harder to spot deception amongst legitimate computations (or the amount of human attention you need to achieve a fixed probability of detection scales according to problem complexity).
You can’t fake failure. Whether it responds in time or not, a trace is provided. That trace, if it validates, provides a record of everything the program did (or rather a randomly selected subset, but that subset is not knowable in advance), even if it didn’t lead to a usable answer. If not valid, you terminate and never run again.
To your second paragraph, these are open questions. But that’s precisely my point—I think MIRI should be engaged in researching these sorts of things, and not be biased towards areas relating to their own preconceived notions of what an AGI experiment should look like.