It’s hard for me to agree or disagree with timeline research being overrated, since I don’t have a great sense of how many total research hours are going into it, but I think Reason #4 is pretty important to this argument and seems wrong. The goodness of these broad strategic goals is pretty insensitive to timelines, but lots of specific actions wind up seeming worth doing or not worth doing based on timelines. I find myself seriously saying something like “Ugh, as usual, it all depends on AI timelines” in conversations about community-building strategy or career decisions like once a week.
For example, in this comment thread about whether and when to do immediately impactful work versus career-capital building, both the shape and the median of the AI x-risk distribution winds up mattering. A more object-level consideration means that “back-loaded” careers like policy look worse relative to “front-loaded” careers like technical research insofar as timelines are earlier.
In community-building, earlier timelines generally supports outreach strategies more focused on finding very promising technical safety researchers; moderate timelines support relatively more focus on policy field-building; and long timelines support more MacAskill-style broad longtermism, moral circle expansion, etc.
Of course, all of this is moot if the questions are superintractable, but I do think additional clarity would turn out to be useful for a pretty broad set of decision-makers—not just top funders or strategy-setters but implementers at the “foot soldier” level of community-building, all the way down to personal career choice.
It’s hard for me to agree or disagree with timeline research being overrated, since I don’t have a great sense of how many total research hours are going into it, but I think Reason #4 is pretty important to this argument and seems wrong. The goodness of these broad strategic goals is pretty insensitive to timelines, but lots of specific actions wind up seeming worth doing or not worth doing based on timelines. I find myself seriously saying something like “Ugh, as usual, it all depends on AI timelines” in conversations about community-building strategy or career decisions like once a week.
For example, in this comment thread about whether and when to do immediately impactful work versus career-capital building, both the shape and the median of the AI x-risk distribution winds up mattering. A more object-level consideration means that “back-loaded” careers like policy look worse relative to “front-loaded” careers like technical research insofar as timelines are earlier.
In community-building, earlier timelines generally supports outreach strategies more focused on finding very promising technical safety researchers; moderate timelines support relatively more focus on policy field-building; and long timelines support more MacAskill-style broad longtermism, moral circle expansion, etc.
Of course, all of this is moot if the questions are super intractable, but I do think additional clarity would turn out to be useful for a pretty broad set of decision-makers—not just top funders or strategy-setters but implementers at the “foot soldier” level of community-building, all the way down to personal career choice.