Another consideration comes to mind: climate change is currently taking up a large amount of attention from competent altruistic people. If the issue were to be solved or its urgency reduced, some of those resources might flow into EA causes.
“[AI safety] is currently taking up a large amount of attention from competent altruistic people. If the issue were to be solved or its urgency reduced, some of those resources might flow into [climate change mitigation]”
If you take this model a step further, it suggests working on whatever the most tractable problem is that others are spending resources on, regardless of its impact, because that will maximally free up energy for other causes.
Sounds like something someone should simulate to see if this effect is strong enough to take into account.
It’s an interesting idea. Often the resource fungibility won’t be huge so it may not make much difference, but in some cases it might.
It also seems to assume that it will use fewer total resources than working on both problems less intensively for a longer period. I would guess that it would usually be more efficient to divide resources and work on problems simultaneously, in part due to diminishing returns to investment. E.g. shifting all AI researchers to climate change would greatly hinder AI research but perhaps not contribute much to climate change mitigation, even assuming good personal fit of researchers, since there are already lots of talented people working on the issue.
But I’ve thought about this for less than 5 minutes so it might deserve a deeper dive. I’m not likely to do it, though.
Another consideration comes to mind: climate change is currently taking up a large amount of attention from competent altruistic people. If the issue were to be solved or its urgency reduced, some of those resources might flow into EA causes.
“[AI safety] is currently taking up a large amount of attention from competent altruistic people. If the issue were to be solved or its urgency reduced, some of those resources might flow into [climate change mitigation]”
So hurry up, Toon ;)
If you take this model a step further, it suggests working on whatever the most tractable problem is that others are spending resources on, regardless of its impact, because that will maximally free up energy for other causes.
Sounds like something someone should simulate to see if this effect is strong enough to take into account.
It’s an interesting idea. Often the resource fungibility won’t be huge so it may not make much difference, but in some cases it might.
It also seems to assume that it will use fewer total resources than working on both problems less intensively for a longer period. I would guess that it would usually be more efficient to divide resources and work on problems simultaneously, in part due to diminishing returns to investment. E.g. shifting all AI researchers to climate change would greatly hinder AI research but perhaps not contribute much to climate change mitigation, even assuming good personal fit of researchers, since there are already lots of talented people working on the issue.
But I’ve thought about this for less than 5 minutes so it might deserve a deeper dive. I’m not likely to do it, though.