A recurring motif in your posts is your willingness to be explicit about your uncertainty regarding the sign of the net impact of certain cause areasā interventions.
When playing the āgameā of estimating an interventionās net impact, EAs typically apply the set of āhouse rulesā within an interventionās cause area, and ignore āgame extensionsā which incorporate rules from other cause areas. Sadly, we often do this even when the āgame extensionsā involve crucial considerations which can and do flip the sign of interventionsā net impact. Examples:
Global health & development charity analyses often ignore population ethics. Under many reasonable beliefs in population ethics, much of these interventionsā impact is on their effect on human population size. This leads to situations where people fund lifesaving charities, which increase the human population, and also fund family planning charities, which reduce the human population.
When charities in global health or farmed animal welfare incorporate that, they often neglect the interventionās effect on wild animals or on the long-term future, either of which can utterly dominate.
You seem to believe that one canāt just play āhouse rulesāāif you want to play this game properly, you have to include all of the game extensions, from the effect of malaria charities on the malaria-carrying mosquitos themselves to the effect of reducing x-risk on long-term future animal welfare. Otherwise, you risk making illegal moves and losing when you think youāre winning.
I think you should further defend this view, perhaps by writing a post which is explicit about it. If this is your view, then a sizeable portion of EA money is currently going to the incinerator each year. (Also, EAs are working against each other by donating to lifesaving charities and family planning charities, among many places.) If some EAs are convinced by your post to switch to your preferred charities, then taking the time to write your post will have been highly cost-effective.
Why do you believe that donating to lifesaving charities is in tension with donating to family planning charities? Preventing early deaths from disease reduces suffering, as does allowing women greater bodily autonomy and preventing unwanted pregnancies.
Thanks for the question! Earlier, Vasco gave a consequentialist response, but Iāll try to give a broader response which might chime for more ethical views.
For you, where does the goodness of a lifesaving charity come from? Saving someoneās life:
Enables them to realize the experience of the rest of their life.
Satisfies their desire to survive and not die.
Alleviates the suffering that would have accompanied their death.
These might all seem like noncontroversial benefits, but how one weights between them can have massive implications for cause prioritization. Many EAs consider point (1) to be the main benefit of saving oneās life. Whether or not youāre a consequentialist, if you had to choose between saving a 10-year-old and a 90-year-old, it seems sensible to choose the 10-year-old, because they have so much more life to experience.
But if point (1) is the main benefit of saving a life, even if points (2) and (3) are sizeable parts of the benefit, adding a person to the human population seems close to as good as saving a life! Youāre enabling another person to live an entire lifeās experience.
However, this bumps against the intuition of the goodness of family planning charities. Preventing an unplanned pregnancy absolutely helps a mother, but itās probably not close to as good as saving her life. (Just ask her if sheād rather die or have an unplanned pregnancy. Most would choose the latter.) But we just argued that the effect of preventing another person from living an entire lifeās experience is close to as bad as preventing a life from being saved.
You can also make this argument in the opposite direction: If family planning charities are good, then this must mean itās okay to prevent a person from living a lifeās experience, or itās at least not as bad as the goodness of supporting their motherās autonomy. This would mean lifesaving charities are much less beneficial than we thought they were.
Thank you for this thorough explanation of your views. I am quite curious as to whether you have ever been pregnant. Of course, many people who have been pregnant are vehemently anti-abortion, but my own personal experience of (wanted) pregnancy made me convinced that forcing someone to carry an unwanted pregnancy to term is a crime against their humanity.[1] If you canāt understand why this might be, I would suggest reading Judith Jarvis Thompsonās violinist paper.
I donāt want to relitigate whether abortion ought to be legal (or encouraged, or funded, or whatever), as I find the fact that my bodily autonomy is up for debate to be somewhat dispiriting, so I am going to bow out of this conversation now, but once again I appreciate your taking the time to explain your viewpoint.
ābut what of the fetusās humanity?ā idk man, the fetus is a possible human and the mother is an actual human, and I think actual humans are more important than possible ones. This is also why Iām not a longtermist.
Youāre very welcome! I appreciate you reading and engaging :)
Iām a male and have not been pregnant. Iām familiar with Thompsonās arguments, and I donāt consider them decisive. Depending upon the weeks from gestation, the fetus may be a possible person, but they may also be an actual person.[1] Either way, as in longtermism, I donāt endorse a moral distinction between possible and actual people.
I respect your decision to bow out, so I wonāt elaborate on these points unless you request me to. Thanks again for your engagement!
āOverall, the evidence, and a balanced reading of that evidence, points towards an immediate and unreflective pain experience mediated by the developing function of the nervous system from as early as 12 weeks.ā Derbyshire, S. W., & Bockmann, J. C. (2020). Reconsidering fetal pain. Journal of Medical Ethics, 46(1), 3ā6. https://āādoi.org/āā10.1136/āāmedethics-2019-105701
Thanks for asking! On the one hand, there is not a tension in the sense that both interventions are decreasing suffering in the short term. On the other hand:
Assuming:
The major driver of the (positive/ānegative) impact of lifesaving and family planning charities is essentially a function of their effect on population size.
Lifesaving charities increase population size, whereas family planning charities decrease it.
There is a tension. If increasing the population size is good (bad), lifesaving charities are good (bad), but family planning charities are bad (good).
Thanks for the explanation! Iām not a consequentialist, and I donāt grant that increasing the population size is good in its own right. If you accept increased population as an intrinsic good I can see why youād see a tension.
Just to clarify, I do not see increasing human population as intrinsically good. I think it increases the welfare of humans in the nearterm (assuming the saved lives are good in expectation), but I am quite uncertain about the effects on animals, and indirect longterm effects. So I do not know whether increasing population is good or bad.
I think attempting to account for every factor is a dead end when those factors themselves have huge uncertainty around them.
e.g.:
Thereās huge uncertainty around whether increasing human population is inherently good or bad.
Thereās huge uncertainty around when a wild animalās life is worth living.
Thereās huge uncertainty about how any given intervention now will positively or negatively affect the far future.
I think when analyses ignore these considerations itās not because theyāre being lazy, itās simply an acknowledgment that itās only worth working with factors we have some certainty about, like that vitamin deficiencies and malaria are almost certainly bad
Let me try to illustrate how I think about this with an example. Imagine the following:
Nearterm effects on humans are equal to 1 in expectation.
This estimate is very resilient, i.e. it will not change much in response to new evidence.
Other effects (on animals and in the longterm) are ā1 k with 50 % likelihood, and 1 k with 50 % likelihood, so they are equal to 0 in expectation.
These estimates are not resilient, and, in response to new evidence, there is a 50 % chance the other effects will be negative in expectation, and 50 % chance they will be positive in expectation.
However, it is very unlikely that the other effects will in expectation be between ā1 and 1, i.e. they will most likely dominate the expected nearterm effects.
What do you think is a better description of our situation?
The expected overall effect is 1 (= 1 + 0) in expectation. This is positive, so the intervention is robustly good.
The overall effects is ā999 (= 1 ā 1 k) with 50 % likelihood, and 1,001 (= 1 + 1 k) with 50 % likelihood. This means the expected value is positive. However, given the lack of resilience of the other effects, we have little idea whether it will continue to be positive, or turn out negative in response to new evidence. So we should not act as if the intervention is robustly good. Instead, it would be good to investigate the other effects further, especially because we have not even tried any hard to do that in the past.
Iām curious: How do you feel about hyperfocused neartermist interventions which alter as little of the rest of the world as possible?
An example of this would be humane slaughter, which shouldnāt have much affect on farmed animal, wild animal, or human populations, other than reducing a farmed animalās suffering at the moment of death.
Itās plausible that certain hyperfocused neartermist interventions can be precisely targeted enough that the overall effect is more like ā1 with 50% likelihood, or 3 with 50% likelihood. A portfolio of independent hyperfocused interventions could be shown to have quite strong robustness.
Thanks for asking! I have not thought much about it, but I feel like neartermist approaches which focus on increasing (animal/āhuman) welfare per individual are more robustly good. Interventions which change human population size will lead to a different number of wild animals, which might dominate the overall nearterm effect while having an unclear sign.
I disagree with the assumption that those +1000/ā-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 youāre trying to account for (e.g. the utility of a wild animalās 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/ābenefits of population growth when assessing the value of vitamin supplementation.
I disagree with the assumption that those +1000/ā-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 GiveWellās 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 youāre trying to account for (e.g. the utility of a wild animalās 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 ACEās top charities, so they are presumably doing something valuable), and Welfare Footprint Projectās research on assessing wild animal welfare.
āestimateā¦ will not change much in response to new informationā 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)
You seem to believe that one canāt just play āhouse rulesāāif you want to play this game properly, you have to include all of the game extensions, from the effect of malaria charities on the malaria-carrying mosquitos themselves to the effect of reducing x-risk on long-term future animal welfare. Otherwise, you risk making illegal moves and losing when you think youāre winning.
Thanks for bringing that post to my attention, and for your excellent post on taking a stand between meta-cause-areas! You provoked a very important conversation.
Thanks for this analysis, Vasco!
A recurring motif in your posts is your willingness to be explicit about your uncertainty regarding the sign of the net impact of certain cause areasā interventions.
When playing the āgameā of estimating an interventionās net impact, EAs typically apply the set of āhouse rulesā within an interventionās cause area, and ignore āgame extensionsā which incorporate rules from other cause areas. Sadly, we often do this even when the āgame extensionsā involve crucial considerations which can and do flip the sign of interventionsā net impact. Examples:
Global health & development charity analyses often ignore population ethics. Under many reasonable beliefs in population ethics, much of these interventionsā impact is on their effect on human population size. This leads to situations where people fund lifesaving charities, which increase the human population, and also fund family planning charities, which reduce the human population.
These analyses often neglect the effect of changing human population size on farmed animals.
When charities in global health or farmed animal welfare incorporate that, they often neglect the interventionās effect on wild animals or on the long-term future, either of which can utterly dominate.
You seem to believe that one canāt just play āhouse rulesāāif you want to play this game properly, you have to include all of the game extensions, from the effect of malaria charities on the malaria-carrying mosquitos themselves to the effect of reducing x-risk on long-term future animal welfare. Otherwise, you risk making illegal moves and losing when you think youāre winning.
I think you should further defend this view, perhaps by writing a post which is explicit about it. If this is your view, then a sizeable portion of EA money is currently going to the incinerator each year. (Also, EAs are working against each other by donating to lifesaving charities and family planning charities, among many places.) If some EAs are convinced by your post to switch to your preferred charities, then taking the time to write your post will have been highly cost-effective.
Why do you believe that donating to lifesaving charities is in tension with donating to family planning charities? Preventing early deaths from disease reduces suffering, as does allowing women greater bodily autonomy and preventing unwanted pregnancies.
Thanks for the question! Earlier, Vasco gave a consequentialist response, but Iāll try to give a broader response which might chime for more ethical views.
For you, where does the goodness of a lifesaving charity come from? Saving someoneās life:
Enables them to realize the experience of the rest of their life.
Satisfies their desire to survive and not die.
Alleviates the suffering that would have accompanied their death.
These might all seem like noncontroversial benefits, but how one weights between them can have massive implications for cause prioritization. Many EAs consider point (1) to be the main benefit of saving oneās life. Whether or not youāre a consequentialist, if you had to choose between saving a 10-year-old and a 90-year-old, it seems sensible to choose the 10-year-old, because they have so much more life to experience.
But if point (1) is the main benefit of saving a life, even if points (2) and (3) are sizeable parts of the benefit, adding a person to the human population seems close to as good as saving a life! Youāre enabling another person to live an entire lifeās experience.
However, this bumps against the intuition of the goodness of family planning charities. Preventing an unplanned pregnancy absolutely helps a mother, but itās probably not close to as good as saving her life. (Just ask her if sheād rather die or have an unplanned pregnancy. Most would choose the latter.) But we just argued that the effect of preventing another person from living an entire lifeās experience is close to as bad as preventing a life from being saved.
You can also make this argument in the opposite direction: If family planning charities are good, then this must mean itās okay to prevent a person from living a lifeās experience, or itās at least not as bad as the goodness of supporting their motherās autonomy. This would mean lifesaving charities are much less beneficial than we thought they were.
(Full disclosure: I take the first perspective, and donāt support family planning charities.)
Thank you for this thorough explanation of your views. I am quite curious as to whether you have ever been pregnant. Of course, many people who have been pregnant are vehemently anti-abortion, but my own personal experience of (wanted) pregnancy made me convinced that forcing someone to carry an unwanted pregnancy to term is a crime against their humanity.[1] If you canāt understand why this might be, I would suggest reading Judith Jarvis Thompsonās violinist paper.
I donāt want to relitigate whether abortion ought to be legal (or encouraged, or funded, or whatever), as I find the fact that my bodily autonomy is up for debate to be somewhat dispiriting, so I am going to bow out of this conversation now, but once again I appreciate your taking the time to explain your viewpoint.
ābut what of the fetusās humanity?ā idk man, the fetus is a possible human and the mother is an actual human, and I think actual humans are more important than possible ones. This is also why Iām not a longtermist.
Youāre very welcome! I appreciate you reading and engaging :)
Iām a male and have not been pregnant. Iām familiar with Thompsonās arguments, and I donāt consider them decisive. Depending upon the weeks from gestation, the fetus may be a possible person, but they may also be an actual person.[1] Either way, as in longtermism, I donāt endorse a moral distinction between possible and actual people.
I respect your decision to bow out, so I wonāt elaborate on these points unless you request me to. Thanks again for your engagement!
āOverall, the evidence, and a balanced reading of that evidence, points towards an immediate and unreflective pain experience mediated by the developing function of the nervous system from as early as 12 weeks.ā Derbyshire, S. W., & Bockmann, J. C. (2020). Reconsidering fetal pain. Journal of Medical Ethics, 46(1), 3ā6. https://āādoi.org/āā10.1136/āāmedethics-2019-105701
Hi britomart,
Thanks for asking! On the one hand, there is not a tension in the sense that both interventions are decreasing suffering in the short term. On the other hand:
Assuming:
The major driver of the (positive/ānegative) impact of lifesaving and family planning charities is essentially a function of their effect on population size.
Lifesaving charities increase population size, whereas family planning charities decrease it.
There is a tension. If increasing the population size is good (bad), lifesaving charities are good (bad), but family planning charities are bad (good).
Thanks for the explanation! Iām not a consequentialist, and I donāt grant that increasing the population size is good in its own right. If you accept increased population as an intrinsic good I can see why youād see a tension.
You are welcome!
Just to clarify, I do not see increasing human population as intrinsically good. I think it increases the welfare of humans in the nearterm (assuming the saved lives are good in expectation), but I am quite uncertain about the effects on animals, and indirect longterm effects. So I do not know whether increasing population is good or bad.
I think attempting to account for every factor is a dead end when those factors themselves have huge uncertainty around them.
e.g.:
Thereās huge uncertainty around whether increasing human population is inherently good or bad.
Thereās huge uncertainty around when a wild animalās life is worth living.
Thereās huge uncertainty about how any given intervention now will positively or negatively affect the far future.
I think when analyses ignore these considerations itās not because theyāre being lazy, itās simply an acknowledgment that itās only worth working with factors we have some certainty about, like that vitamin deficiencies and malaria are almost certainly bad
Thanks for engaging, Henry!
Let me try to illustrate how I think about this with an example. Imagine the following:
Nearterm effects on humans are equal to 1 in expectation.
This estimate is very resilient, i.e. it will not change much in response to new evidence.
Other effects (on animals and in the longterm) are ā1 k with 50 % likelihood, and 1 k with 50 % likelihood, so they are equal to 0 in expectation.
These estimates are not resilient, and, in response to new evidence, there is a 50 % chance the other effects will be negative in expectation, and 50 % chance they will be positive in expectation.
However, it is very unlikely that the other effects will in expectation be between ā1 and 1, i.e. they will most likely dominate the expected nearterm effects.
What do you think is a better description of our situation?
The expected overall effect is 1 (= 1 + 0) in expectation. This is positive, so the intervention is robustly good.
The overall effects is ā999 (= 1 ā 1 k) with 50 % likelihood, and 1,001 (= 1 + 1 k) with 50 % likelihood. This means the expected value is positive. However, given the lack of resilience of the other effects, we have little idea whether it will continue to be positive, or turn out negative in response to new evidence. So we should not act as if the intervention is robustly good. Instead, it would be good to investigate the other effects further, especially because we have not even tried any hard to do that in the past.
Iām curious: How do you feel about hyperfocused neartermist interventions which alter as little of the rest of the world as possible?
An example of this would be humane slaughter, which shouldnāt have much affect on farmed animal, wild animal, or human populations, other than reducing a farmed animalās suffering at the moment of death.
Itās plausible that certain hyperfocused neartermist interventions can be precisely targeted enough that the overall effect is more like ā1 with 50% likelihood, or 3 with 50% likelihood. A portfolio of independent hyperfocused interventions could be shown to have quite strong robustness.
Thanks for asking! I have not thought much about it, but I feel like neartermist approaches which focus on increasing (animal/āhuman) welfare per individual are more robustly good. Interventions which change human population size will lead to a different number of wild animals, which might dominate the overall nearterm effect while having an unclear sign.
I disagree with the assumption that those +1000/ā-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 youāre trying to account for (e.g. the utility of a wild animalās 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/ābenefits 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 GiveWellās 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 ACEās top charities, so they are presumably doing something valuable), and Welfare Footprint Projectās research on assessing wild animal welfare.
āestimateā¦ will not change much in response to new informationā 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)
Hi Ariel,
Joey just brought to my attention the post The Importance of Intercausal Impacts by Sebastian Joy.
Thanks for bringing that post to my attention, and for your excellent post on taking a stand between meta-cause-areas! You provoked a very important conversation.
Thanks for that comment, Ariel! I think you described my view quite well, and I do agree I should probably try to write a post about it.
Great point.