I disagree with the assumption that those +1000/-1000 longterm effects can be known with any certainty, no matter how many resources you spend on studying them.
The world is a chaotic system. Trying to predict where the storm will land as the butterfly flaps its wings is unreasonable. Also, some of the measures you’re trying to account for (e.g. the utility of a wild animal’s life) are probably not even measurable. The combination of these two difficulties makes me very dubious about the value of trying to do things like factor in long-term mosquito wellbeing to bednet effectiveness calculations, or trying to account for the far-future risks/benefits of population growth when assessing the value of vitamin supplementation.
I disagree with the assumption that those +1000/-1000 longterm effects can be known with any certainty, no matter many resources you spend on studying them.
I agree there will always be lots of uncertainty, even after spending tons of resources investigating the longterm effects. However, we do not need to be certain about the longterm effects. We only have to study them enough to ensure our best estimate of their expected value is resilient, i.e. that it will not change much in response to new information.
If people at Open Philanthropy and Rethink Priorities spent 10 kh researching the animal and longterm effects of GiveWell’s top charities, are you confident their best estimate for the expected animal and longterm effects would be negligible in comparison with the expected nearterm human effects? I am quite open to this possibility, but I do not understand how it is possible to be confident either way, given very little research has been done so far on animal and longterm effects.
The world is a chaotic system, trying to predict where the storm will land as the butterfly flaps its wings is unreasonably.
A butterfly flapping its wings can cause a storm, but it can just as well prevent a storm. These are cases of simple cluelessness in which there is evidential symmetry, so they are not problematic. The animal and longterm effects of saving lives are not symmetric in that way. For example, we can predict that humans work and eat, so increasing population will tend to grow the economy and food production.
Also, some of the measures you’re trying to account for (e.g. the utility of a wild animal’s life) are probably not even measurable.
For intuitions that measuring wild animal welfare is not impossible, you can check research from Wild Animal Initiative (one of ACE’s top charities, so they are presumably doing something valuable), and Welfare Footprint Project’s research on assessing wild animal welfare.
“estimate… will not change much in response to new information” seems like the definition of certainty.
It seems very optimistic to think that by doing enough calculations and data analysis we can overcome the butterfly effect. Even your example of the correlation between population and economic growth is difficult to predict (e.g. Concentrating wealth by reducing family size might have positive effects on economic growth)
I disagree with the assumption that those +1000/-1000 longterm effects can be known with any certainty, no matter how many resources you spend on studying them.
The world is a chaotic system. Trying to predict where the storm will land as the butterfly flaps its wings is unreasonable. Also, some of the measures you’re trying to account for (e.g. the utility of a wild animal’s life) are probably not even measurable. The combination of these two difficulties makes me very dubious about the value of trying to do things like factor in long-term mosquito wellbeing to bednet effectiveness calculations, or trying to account for the far-future risks/benefits of population growth when assessing the value of vitamin supplementation.
Thanks for following up!
I agree there will always be lots of uncertainty, even after spending tons of resources investigating the longterm effects. However, we do not need to be certain about the longterm effects. We only have to study them enough to ensure our best estimate of their expected value is resilient, i.e. that it will not change much in response to new information.
If people at Open Philanthropy and Rethink Priorities spent 10 kh researching the animal and longterm effects of GiveWell’s top charities, are you confident their best estimate for the expected animal and longterm effects would be negligible in comparison with the expected nearterm human effects? I am quite open to this possibility, but I do not understand how it is possible to be confident either way, given very little research has been done so far on animal and longterm effects.
A butterfly flapping its wings can cause a storm, but it can just as well prevent a storm. These are cases of simple cluelessness in which there is evidential symmetry, so they are not problematic. The animal and longterm effects of saving lives are not symmetric in that way. For example, we can predict that humans work and eat, so increasing population will tend to grow the economy and food production.
For intuitions that measuring wild animal welfare is not impossible, you can check research from Wild Animal Initiative (one of ACE’s top charities, so they are presumably doing something valuable), and Welfare Footprint Project’s research on assessing wild animal welfare.
“estimate… will not change much in response to new information” seems like the definition of certainty.
It seems very optimistic to think that by doing enough calculations and data analysis we can overcome the butterfly effect. Even your example of the correlation between population and economic growth is difficult to predict (e.g. Concentrating wealth by reducing family size might have positive effects on economic growth)