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  text: 'We can imagine two regimes of this problem: in the weak regime the AI may make a small number of errors based on its beliefs about simulations, and so as long as we actually correct these errors, what you called "directly hit the sense switch," we can bound the total damage. Even in the weak regime we should be careful that a small number of errors can't do damage, which is still a very hard constraint. (Since these errors can occur simultaneously in every different prediction system, and can persist until a human actually intervenes to correct them.) I think this problem is very common and that a similar engineering constraint arises for a number of less weird reasons.\r  \n\r  \nIn the strong regime, our AI is very convinced that it is in a simulation (99.999%, say), and so it can potentially make tens of thousands of errors. This would be very dire, but I would classify it is as a failure of learning (after the hundredth time that it turns out to not be in a simulation after predicting that it was, we hope that our AI can learn the general principle "I'm not in a simulation").',
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