Do you think that we can consider this as its own problem, of technology outpacing philosophy, which we can evaluate separately of other aspects of AI risk? Or are these problems tied together in a critical way?
In the past people have argued that we needed to resole a wide range of philosophical questions prior to constructing AI because we would need to lock in answers to those questions at that point. I would like to push back against that view, while acknowledging that there may be object-level issues where we pay a costs because we lack philosophical understanding (e.g. how to trade off haste vs. extinction risk, how to deal with the possibility of strange physics, how to bargain effectively...). And I would further acknowledge that AI may have a differential effect on progress in physical technology vs. philosophy.
My current tentative view is that the total object-level cost from philosophical error is modest over the next subjective century. I also believe that you overestimate the differential effects of AI, but that’s also not very firm. If my view changed on these points it might make me more enthusiastic about philosophy or metaphilosophy as research projects.
I have a much stronger belief that we should treat metaphilosophy and AI control as separate problems, and in particular that these concerns about metaphilosophy should not significantly dampen my enthusiasm for my current approach to resolving control problems.
I agree with the sentiment that there are philosophical difficulties that AI needs to take into account, but that very likely take far too long to formulate. Simpler kinds of indirect normativity that involve prediction of uploads allow delaying that work to after AI.
So this issue doesn’t block all actionable work, as its straightforward form would suggest. There might be no need for the activities to be in this order in physical time. Instead it motivates work on the simpler kinds of indirect normativity that would allow such philosophical investigations to take place inside AI’s values. In particular, it motivates figuring out what kind of thing AI’s values are, in sufficient generality so that it would be able to represent the results of unexpected future philosophical progress.
If we could model humans as having well-defined values but irrational in predictable ways (e.g., due to computational constraints or having a limited repertoire of heuristics), then some variant of CIRL might be sufficient (along with solving certain other technical problems such as corrigibility and preventing bugs) for creating aligned AIs. I was (and still am) worried that some researchers think this is actually true, or by not mentioning further difficulties, give the wrong impression to policymakers and other researchers.
If you are already aware of the philosophical/metaphilosophical problems mentioned here, and have an approach that you think can work despite them, then it’s not my intention to dampen your enthusiasm. We may differ on how much expected value we think your approach can deliver, but I don’t really know another approach that you can more productively spend your time on.
Do you think that we can consider this as its own problem, of technology outpacing philosophy, which we can evaluate separately of other aspects of AI risk? Or are these problems tied together in a critical way?
In the past people have argued that we needed to resole a wide range of philosophical questions prior to constructing AI because we would need to lock in answers to those questions at that point. I would like to push back against that view, while acknowledging that there may be object-level issues where we pay a costs because we lack philosophical understanding (e.g. how to trade off haste vs. extinction risk, how to deal with the possibility of strange physics, how to bargain effectively...). And I would further acknowledge that AI may have a differential effect on progress in physical technology vs. philosophy.
My current tentative view is that the total object-level cost from philosophical error is modest over the next subjective century. I also believe that you overestimate the differential effects of AI, but that’s also not very firm. If my view changed on these points it might make me more enthusiastic about philosophy or metaphilosophy as research projects.
I have a much stronger belief that we should treat metaphilosophy and AI control as separate problems, and in particular that these concerns about metaphilosophy should not significantly dampen my enthusiasm for my current approach to resolving control problems.
I agree with the sentiment that there are philosophical difficulties that AI needs to take into account, but that very likely take far too long to formulate. Simpler kinds of indirect normativity that involve prediction of uploads allow delaying that work to after AI.
So this issue doesn’t block all actionable work, as its straightforward form would suggest. There might be no need for the activities to be in this order in physical time. Instead it motivates work on the simpler kinds of indirect normativity that would allow such philosophical investigations to take place inside AI’s values. In particular, it motivates figuring out what kind of thing AI’s values are, in sufficient generality so that it would be able to represent the results of unexpected future philosophical progress.
If we could model humans as having well-defined values but irrational in predictable ways (e.g., due to computational constraints or having a limited repertoire of heuristics), then some variant of CIRL might be sufficient (along with solving certain other technical problems such as corrigibility and preventing bugs) for creating aligned AIs. I was (and still am) worried that some researchers think this is actually true, or by not mentioning further difficulties, give the wrong impression to policymakers and other researchers.
If you are already aware of the philosophical/metaphilosophical problems mentioned here, and have an approach that you think can work despite them, then it’s not my intention to dampen your enthusiasm. We may differ on how much expected value we think your approach can deliver, but I don’t really know another approach that you can more productively spend your time on.