My impression of the plurality perspective around here is that the examples you give (e.g. overweighting contemporary ideology, reinforcing non-truth-seeking discourse patterns, and people accidentally damaging themselves with AI-enabled exotic experiences) are considered unfortunate but acceptable defects in a “safe” transition to a world with superintelligences. These scenarios don’t violate existential safety because something that is still recognizably humanity has survived (perhaps even more recognizably human than you and I would hope for).
I agree with your sense that these are salient bad outcomes, but I think they can only be considered “existentially bad” if they plausibly get “locked-in,” i.e. persist throughout a substantial fraction of some exponentially-discounted future light-cone. I think Paul’s argument amounts to saying that a corrigibility approach focuses directly on mitigating the “lock-in” of wrong preferences, whereas ambitious value learning would try to get the right preferences but has a greater risk of locking-in its best guess.
I think Paul’s argument amounts to saying that a corrigibility approach focuses directly on mitigating the “lock-in” of wrong preferences, whereas ambitious value learning would try to get the right preferences but has a greater risk of locking-in its best guess.
What’s the actual content of the argument that this is true? From my current perspective, corrigible AI still has a very high risk of lock-in of wrong preferences, due to bad metapreferences of the overseer, and ambitious value learning, or some ways of doing that, could turn out to be less risky with respect to lock-in, because for example you could potentially examine the metapreferences that a value-learning AI has learned, which might make it more obvious that they’re not safe enough as is, triggering attempts to do something about that.
My impression of the plurality perspective around here is that the examples you give (e.g. overweighting contemporary ideology, reinforcing non-truth-seeking discourse patterns, and people accidentally damaging themselves with AI-enabled exotic experiences) are considered unfortunate but acceptable defects in a “safe” transition to a world with superintelligences. These scenarios don’t violate existential safety because something that is still recognizably humanity has survived (perhaps even more recognizably human than you and I would hope for).
I agree with your sense that these are salient bad outcomes, but I think they can only be considered “existentially bad” if they plausibly get “locked-in,” i.e. persist throughout a substantial fraction of some exponentially-discounted future light-cone. I think Paul’s argument amounts to saying that a corrigibility approach focuses directly on mitigating the “lock-in” of wrong preferences, whereas ambitious value learning would try to get the right preferences but has a greater risk of locking-in its best guess.
What’s the actual content of the argument that this is true? From my current perspective, corrigible AI still has a very high risk of lock-in of wrong preferences, due to bad metapreferences of the overseer, and ambitious value learning, or some ways of doing that, could turn out to be less risky with respect to lock-in, because for example you could potentially examine the metapreferences that a value-learning AI has learned, which might make it more obvious that they’re not safe enough as is, triggering attempts to do something about that.