I think the overall approach youâve taken is good, and itâs cool to see youâve worked through this. This is also the kind of example I had in mind, although I didnât bother to work with estimates.
I do think it would be better to use some projections for animal product consumption and fertility rates in the regions MC works in (I expect consumption per capita to increase and fertility to decrease) to include effects of descendants and changing consumption habits, since these plausibly could end up dominating the effects of MC, or at least on animals (and you also have to decide on your population ethics: does the happiness of the additional descendants contribute to the good compared to if they were never born?). Then, there are also timelines for alternatives proteins (e.g. here), but these are much more speculative to me.
I also personally worry that cage-free campaigns could be net negative in expectation (at least in the short-term, without further improvements), mostly since on-farm mortality rates are higher in cage-free systems. See some context and further discussion here. I believe that corporate campaigns work, though, so I think we could come up with a target for a corporate campaign that weâd expect to be robustly positive for animals. I think work for more humane slaughter is robustly positive. Family planning interventions might be the most promising, see this new charity incubated by Charity Entrepreneurship and their supporting report, including their estimated cost-effectiveness of:
â$144 per unintended birth avertedâ, and
â377 welfare points gained per dollar spentâ for farmed animals. (I donât know off-hand if theyâre including descendants or projected changes in consumption in this figure.)
However, this new charity doesnât have any track record yet, so itâs in some ways more speculative than GiveWell charities or THL. CE does use success probabilities in their models, but this is a parameter that you might want to do a sensitivity analysis to. (Disclosure: Iâm an animal welfare research intern for Charity Entrepreneurship.)
Thanks for your thoughts and the links. I agree that more consideration of long-term effects and population ethics seems important (also, I would have thought, for the impact of accelerating animal welfare improvements). I donât know anything to go on for quantitative estimates of long-term effects myself, though.
Regarding the possibility of cage-free campaigns as being net negative, I agree this sounds like a risk, so perhaps I was loose in saying donating a certain amount to THL could be ârobustly betterâ. Iâm not sure itâs going to be possible to be 100% sure that any set of interventions wonât have a negative impact, thoughâI was basically going for being able to feel âquite confidentâ that the impact on farmed animals wouldnât be negative (edit: given the assumptions Iâve madeâall things considered Iâm not as confident as that), and havenât been able yet to be precise about what that means.
Thinking about it, in general, it seems to me that the ranges of possible effects of interventions could be unbounded, so then youâd have to accept some chance of having a negative impact in the corresponding cause areas. Perhaps this is something your general framework could be augmented to take into account e.g. could one set a maximum allowed probability of having a negative effect in one cause area, or would it be sufficient to have a positive expected effect in each area?
Thinking about it, in general, it seems to me that the ranges of possible effects of interventions could be unbounded, so then youâd have to accept some chance of having a negative impact in the corresponding cause areas. Perhaps this is something your general framework could be augmented to take into account e.g. could one set a maximum allowed probability of having a negative effect in one cause area, or would it be sufficient to have a positive expected effect in each area?
So, itâs worth distinguishing between
quantified uncertainty, or, risk, when you can put a single probability on something, and
unquantified uncertainty, when you canât decide among multiple probabilities).
If thereâs a quantified risk of negative, but your expected value is positive under all of the worldviews you find plausible enough to consider anyway (e.g. for all cause areas), then youâre still okay under the framework I propose in this post. I am effectively suggesting that itâs sufficient to have a positive expected effect in each area (although there may be important considerations that go beyond cause areas).
However, you might have enough cluelessness that you canât find any portfolio thatâs positive in expected value under all plausible worldviews like this. That would suck, but I would normally accept continuing to look for robustly positive expected value portfolios as a good option (whether or not it is robustly positive).
I think the overall approach youâve taken is good, and itâs cool to see youâve worked through this. This is also the kind of example I had in mind, although I didnât bother to work with estimates.
I do think it would be better to use some projections for animal product consumption and fertility rates in the regions MC works in (I expect consumption per capita to increase and fertility to decrease) to include effects of descendants and changing consumption habits, since these plausibly could end up dominating the effects of MC, or at least on animals (and you also have to decide on your population ethics: does the happiness of the additional descendants contribute to the good compared to if they were never born?). Then, there are also timelines for alternatives proteins (e.g. here), but these are much more speculative to me.
I also personally worry that cage-free campaigns could be net negative in expectation (at least in the short-term, without further improvements), mostly since on-farm mortality rates are higher in cage-free systems. See some context and further discussion here. I believe that corporate campaigns work, though, so I think we could come up with a target for a corporate campaign that weâd expect to be robustly positive for animals. I think work for more humane slaughter is robustly positive. Family planning interventions might be the most promising, see this new charity incubated by Charity Entrepreneurship and their supporting report, including their estimated cost-effectiveness of:
â$144 per unintended birth avertedâ, and
â377 welfare points gained per dollar spentâ for farmed animals. (I donât know off-hand if theyâre including descendants or projected changes in consumption in this figure.)
However, this new charity doesnât have any track record yet, so itâs in some ways more speculative than GiveWell charities or THL. CE does use success probabilities in their models, but this is a parameter that you might want to do a sensitivity analysis to. (Disclosure: Iâm an animal welfare research intern for Charity Entrepreneurship.)
Finally, Founders Pledge did a direct comparison between THL and AMF, including sensitivity analysis to moral weights, that might be useful.
Thanks for your thoughts and the links. I agree that more consideration of long-term effects and population ethics seems important (also, I would have thought, for the impact of accelerating animal welfare improvements). I donât know anything to go on for quantitative estimates of long-term effects myself, though.
Regarding the possibility of cage-free campaigns as being net negative, I agree this sounds like a risk, so perhaps I was loose in saying donating a certain amount to THL could be ârobustly betterâ. Iâm not sure itâs going to be possible to be 100% sure that any set of interventions wonât have a negative impact, thoughâI was basically going for being able to feel âquite confidentâ that the impact on farmed animals wouldnât be negative (edit: given the assumptions Iâve madeâall things considered Iâm not as confident as that), and havenât been able yet to be precise about what that means.
Thinking about it, in general, it seems to me that the ranges of possible effects of interventions could be unbounded, so then youâd have to accept some chance of having a negative impact in the corresponding cause areas. Perhaps this is something your general framework could be augmented to take into account e.g. could one set a maximum allowed probability of having a negative effect in one cause area, or would it be sufficient to have a positive expected effect in each area?
So, itâs worth distinguishing between
quantified uncertainty, or, risk, when you can put a single probability on something, and
unquantified uncertainty, when you canât decide among multiple probabilities).
If thereâs a quantified risk of negative, but your expected value is positive under all of the worldviews you find plausible enough to consider anyway (e.g. for all cause areas), then youâre still okay under the framework I propose in this post. I am effectively suggesting that itâs sufficient to have a positive expected effect in each area (although there may be important considerations that go beyond cause areas).
However, you might have enough cluelessness that you canât find any portfolio thatâs positive in expected value under all plausible worldviews like this. That would suck, but I would normally accept continuing to look for robustly positive expected value portfolios as a good option (whether or not it is robustly positive).