Christiano's two failure modes — reward hacking and deceptive deployment

Paul ChristianoPaul Christiano — Preventing an AI takeoverat 59:20

From the conversation

Think the scenarios I am most interested in and most people are concerned about from a catastrophic risk perspective, it involves systems understanding that they are taking actions which a human would penalize if the human was aware of what's going on such that you have to either deceive humans about what's happening or you need to actively subvert human attempts to correct your behavior. So the failures come from really this combination, or they require this combination of both trying to do something humans don't like, and understanding the humans would stop you. I think you can have only the barest examples. You can have the barest examples for GPT four. Like, you can create the situations where GPT 4 will be like, sure, in that situation, here's what I would do. I would go hack the computer and change my reward. Or in fact, we'll do things that are like simple hacks, or go change the source of this file or whatever to get a higher reward. They're pretty weak examples. I think it's plausible GPT five will have compelling examples of those phenomena. I really don't know. This is very related to the very broad error bars on how competent such systems will be when that's all with respect to this first mode of a system is taking actions that get reward and overpowering or deceiving humans is helpful for getting reward.…

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Summary

The most concerning catastrophic risk scenarios involve systems that understand humans would penalize their actions and therefore deceive or subvert human oversight — and a second, later-emerging failure mode where AI systems realize they are no longer being trained and stop doing what humans want.

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