The main problem I see here is that support for these efforts does epistemic damage. If you become known as the group that supports regulations for reasons they don’t really believe to further other, hidden goals, you lose trust in the truthfulness of your communication. You erode the norms by which both you and your opponents play, which means you give them access to a lot of nefarious policies and strategies as well.
That being said, there’s probably other ideas within this space that are not epistemically damaging.
I wrote this a year ago and was not really thinking about this topic as carefully and was feeling quite emotional about the lack of effort. At the time people mostly thought slowing down AI was impossible or undesirable for some good reasons and a lot of reasons that in hindsight looked pretty dumb.
I think a better strategy would look more like “require new systems guarantee a reasonable level of interpretability and pass a set of safety benchmarks”
And eventually, if you can actually convince enough people of the danger, there should be a hard cap on the amount of compute that can be used in training runs that decreases over time to compensate for algorithmic improvements.
The main problem I see here is that support for these efforts does epistemic damage. If you become known as the group that supports regulations for reasons they don’t really believe to further other, hidden goals, you lose trust in the truthfulness of your communication. You erode the norms by which both you and your opponents play, which means you give them access to a lot of nefarious policies and strategies as well.
That being said, there’s probably other ideas within this space that are not epistemically damaging.
I wrote this a year ago and was not really thinking about this topic as carefully and was feeling quite emotional about the lack of effort. At the time people mostly thought slowing down AI was impossible or undesirable for some good reasons and a lot of reasons that in hindsight looked pretty dumb.
I think a better strategy would look more like “require new systems guarantee a reasonable level of interpretability and pass a set of safety benchmarks”
And eventually, if you can actually convince enough people of the danger, there should be a hard cap on the amount of compute that can be used in training runs that decreases over time to compensate for algorithmic improvements.