I now think principles-first EA is more important than I previously thought because it helps prevent effectiveness drift. My anecdotal evidence from AI Safety and especially biosecurity gives me the impression that without constant anchoring to EA and especially comparisons to the clear ToCs and tractability for e.g. AMF, it is easy to lose focus on the high demands of choosing x-risk as a cause area over others. I previously placed less value on having strong links between EA and the various cause areas but now think I should update to thinking strong, continuous engagement with EA is important to keep one’s focus on each intervention’s cause prioritization assumptions that make it comparable to e.g. AMF or cage free chicken campaigns. This is not to say that causes such as AI Safety and biosec are not important, but that unless constantly tied back to EA cause prioritization, there is risk of drifting away from what made the cause look good in the first place. An example from biosecurity is the very easy slippage away from human extinction scenarios to ones where nearly everone dies (the difference being a crux as it is the potentially enormous future one is saving, not the people living at the time of the catastrophe). That said, it is completely fine and commendable that there is AI Safety and biosecurity work that does not target existential threats, but for EAs such changes in the nature of the work means they should consider changing their career. I think this is also important for newcomers to EA: For those of us who were around when we discussed whether x-risks demanded attention we might take concepts such as Pascal’s Mugging as obvious, but for newcomers it is important to engage with such concepts. Another observation I have made is that in animal welfare and global health one is constantly reminded by metrics of suffering alleviated per dollar, but such recurring reminders are lacking in x-risk focused cause areas.
Relatedly, I have met people doing “AI safety” stuff without having impact in mind, and end up doing research on whatever shiny academic vaguely related topic without a clear theory of change, while still being intermingled with the EA crowd sociologically.
Some of them pay lip service to impact and write theories of change to get funds (as a pure mathematician, we do that in my line of work and I think I can recognize when you say there is impact to get the research you are obsessed with funded, and when you are actually trying to do good in the world).
I think oftentimes the relevant counterfactual is not “this person would be doing even more impactful work in a highly-impactful area” but “this person would not be working in a high-impact area whatsoever”
I now think principles-first EA is more important than I previously thought because it helps prevent effectiveness drift. My anecdotal evidence from AI Safety and especially biosecurity gives me the impression that without constant anchoring to EA and especially comparisons to the clear ToCs and tractability for e.g. AMF, it is easy to lose focus on the high demands of choosing x-risk as a cause area over others. I previously placed less value on having strong links between EA and the various cause areas but now think I should update to thinking strong, continuous engagement with EA is important to keep one’s focus on each intervention’s cause prioritization assumptions that make it comparable to e.g. AMF or cage free chicken campaigns. This is not to say that causes such as AI Safety and biosec are not important, but that unless constantly tied back to EA cause prioritization, there is risk of drifting away from what made the cause look good in the first place. An example from biosecurity is the very easy slippage away from human extinction scenarios to ones where nearly everone dies (the difference being a crux as it is the potentially enormous future one is saving, not the people living at the time of the catastrophe). That said, it is completely fine and commendable that there is AI Safety and biosecurity work that does not target existential threats, but for EAs such changes in the nature of the work means they should consider changing their career. I think this is also important for newcomers to EA: For those of us who were around when we discussed whether x-risks demanded attention we might take concepts such as Pascal’s Mugging as obvious, but for newcomers it is important to engage with such concepts. Another observation I have made is that in animal welfare and global health one is constantly reminded by metrics of suffering alleviated per dollar, but such recurring reminders are lacking in x-risk focused cause areas.
Relatedly, I have met people doing “AI safety” stuff without having impact in mind, and end up doing research on whatever shiny academic vaguely related topic without a clear theory of change, while still being intermingled with the EA crowd sociologically.
Some of them pay lip service to impact and write theories of change to get funds (as a pure mathematician, we do that in my line of work and I think I can recognize when you say there is impact to get the research you are obsessed with funded, and when you are actually trying to do good in the world).
I think oftentimes the relevant counterfactual is not “this person would be doing even more impactful work in a highly-impactful area” but “this person would not be working in a high-impact area whatsoever”