I hear two conflicting voices in my head, and in EA:
- Voice: it's highly uncertain whether deworming is effective, based on 20 years of research, randomized controlled trials, and lots of feedback. In fact, many development interventions have a small or negative impact.
- Same voice: we are confident that work for improving the far future is effective, based on <insert argument involving the number of stars in the universe>.
I believe that I could become convinced to work on artificial intelligence or extinction risk reduction. My main crux is that these problems seem intractable. I am worried that my work would have a negligible or a negative impact.
These questions are not sufficiently addressed yet, in my opinion. So far, I've seen mainly vague recommendations (e.g., "community building work does not increase risks" or "look at the success of nuclear disarmament"). Examples of existing work for improving the far future often feel very indirect (e.g., "build a tool to better estimate probabilities ⇒ make better decisions ⇒ facilitate better coordination ⇒ reduce the likelihood of conflict ⇒ prevent a global war ⇒ avoid extinction") and thus disconnected from actual benefits for humanity.
One could argue that uncertainty is not a problem, that it is negligible when considering the huge potential benefit of work for the far future. Moreover, impact is fat-tailed, and thus the expected value dominated by a few really impactful projects, and thus it's worth trying projects even if they have low success probability[1]. This makes sense, but only if we can protect against large negative impacts. I doubt we really can — for example, a case can be made that even safety-focused AI researchers accelerate AI and thus increase its risks.[2]
One could argue that community building or writing "what we owe the future" are concrete ways to do good for the future . Yet this seems to shift the problem rather than solve it. Consider a community builder who convinces 100 people to work on improving the far future. There are now 100 people doing work with uncertain, possibly-negative impact. The community builder's impact is some function which is similarly uncertain and possibly negative. This is especially true if is fat-tailed, as the impact will be dominated by the most successful (or most destructive) people.
To summarize: How can we reliably improve the far future, given that even near-termist work like deworming, with plenty of available data and research and rapid feedback loops and simple theories, so often fails? As someone who is eager to do spend my work time well, who thinks that our moral circle should include the future, but who does not know ways to reliably improve it... what should I do?
Will MacAskill on fat-tailed impact distribution: https://youtu.be/olX_5WSnBwk?t=695 ↩︎
For examples on this forum, see When is AI safety research harmful? or What harm could AI safety do? ↩︎
Thanks a lot for your responses!
I share your sentiment: there must be some form of alignment work that is not speeding up capabilities, some form of longtermist work that isn't risky... right?
Why are the examples so elusive? I think this is the core of the present forum post.
15 years ago, when GiveWell started, the search for good interventions was difficult. It required a lot of research, trials, reasoning etc. to find the current recommendations. We are at a similar point for work targeting the far future... except that we can't do experiments, don't have feedback, don't have historical examples[1], etc. This makes the question a much harder one. It also means that "do research on good interventions" isn't a good answer either, since this research is so intractable.
Ian Morris in this podcast episode discusses to what degree history is contingent, i.e., past events have influenced the future for a long time. ↩︎