Good question! I think this change will be net positive for founder talent.
Firstly I think that in practice there is less competition for the same talent than one might expect:
(1) The talent pools are actually pretty different. Many of the people who are drawn to our incubation program specifically want to be founders, not staff. Conversely, often when a founder comes to work at AIM it’s because they don’t want to be founding at that time.
(2) AIM can’t actually absorb many founders. We’re increasingly specialized, meaning there are fewer and fewer roles a generalist founder could fill.
A relevant stat: Currently 4 out of 20+ staff are former CEIP founders (and 3 out of 4 are in the Programs Team -- where founding experience matters most)
(3) Hopefully the new salary policy will attract more talent to the AIM ecosystem, such that (a) AIM would have less need to hire people who would otherwise found, and (b) more new founders are unlocked than AIM is capable of absorbing.
It's very fair to be concerned that your donations might be doing harm -- I can relate! A bittersweet consolation might be that this is a risk that applies to basically every charitable intervention, including highly evidence-based global health and development interventions. Something that increases a woman's income or autonomy can put her at greater risk of domestic violence for example. Changing someone's life can have impacts on the local and macro-economy, on those impacted by their diet and consumption patterns etc. -- the world is complicated and the risk of doing harm instead of good is always there.
This isn't to say we shouldn't work really hard to understand and prevent such harm! Just that "no chance of harm" is not a realistic bar to aim for
"If there had been 50 studies which compared mortality between two global health intervention and overall results was unequivocal, we would probably conclude that there was no major difference between the two, rather than say we didn't have a clear answer and needed more research." -- True, but the goal of cage-free isn't reducing mortality, it's reducing suffering. Mortality is one possible (but deeply confounded) indicator of suffering we can look at. If, when doing so, we conclude that there is no major difference between mortality in caged and cage-free systems, this has little to no bearing on whether cage-free reduces suffering.
We vibecoded an app script to do it in Google Sheets at AIM, and there’s Guesstimate and the other one (I forget its name). So I agree that it’s easy to do this and people should do so more!
Got it, makes sense. I'm not sure it makes sense to think of these pain levels as discrete categories, but I think your point holds even if we're just using them to gesture at rough areas on a spectrum
“There are good reasons that some of the most rigorous organizations in the space (CG) have made cage-free a top priority and ex ante you should think it unlikely that they all converged without good reasons” — I agree, with the caveat that sometimes what looks like (A) converging opinions of a number of thoughtful actors is actually (B) a chain of deference where one actor has thought about it, and a second actor defers to them, and a third defers to the first two etc, with the nuance and uncertainty getting lost a bit more at every step in the chain. It can be hard to tell A and B apart from the outside
Oh right got it. Thank you. But if (I emphasize: IF) we thought cage-free was negative we could choose to not do that bit right? The sign of the overall portfolio doesn’t seem relevant to that decision
I agree with the other, secondary Aidan’s comment (I am the original and true Aidan).
A common journey with EA is going from (1) not thinking we can know whether charity is helping or that it makes a difference which charity you choose to (2) learning about EA and being thrilled to discover that we can know and some charities are excellent to (3) getting into the weeds of the empirical and ethical uncertainties around the first, 2nd and nth order effects of a certain cause area and becoming disillusioned and pivoting to another cause to (4) realising that every cause is fraught with uncertainty and starting to feel a bit jaded about charity to (5) accepting that the world is super uncertain but that the expected impact of the best bets we have is promising enough to motivate ongoing work on them (especially if we double down on generating more primary evidence and doing good M&E to make our uncertainty go down with time)
I hope we don’t lose you at the 4th step ❤️
(This is not to say that all causes are equally uncertain, or that it’s guaranteed that the best bets in any particular cause will be compelling enough for you)
I really appreciate this post and am also very excited to see more primary research. In addition to the uncertainty about how a given change in farming practices impacts welfare, I think whether or not those changes are actually occurring is highly uncertain, and I’d like to see a greater investment in M&E at animal orgs to validate this.
More primary research could be complementary to this, for example, better monitoring of welfare indicators on farms and/or at slaughter could allow us to see whether the welfare is actually improving, which requires both that the intervention is actually occurring and that it’s helping animals when it occurs.
I do wonder about our ability to measure harms like stress and fear though. I think focusing just on mortality or health conditions might lead us to make false conclusions about which farming practices are better for animals. Does anyone know anything about our capacity to measure psychological distress from deprivation of natural behaviors vs fear of violence for example? (the former being one that drives a significant amount of the improvement that cage-free brings according to WFI, the latter being one Amanda points to being absent and potentially outweighing the former)
Good question! I think this change will be net positive for founder talent.
Firstly I think that in practice there is less competition for the same talent than one might expect:
(1) The talent pools are actually pretty different. Many of the people who are drawn to our incubation program specifically want to be founders, not staff. Conversely, often when a founder comes to work at AIM it’s because they don’t want to be founding at that time.
(2) AIM can’t actually absorb many founders. We’re increasingly specialized, meaning there are fewer and fewer roles a generalist founder could fill.
A relevant stat: Currently 4 out of 20+ staff are former CEIP founders (and 3 out of 4 are in the Programs Team -- where founding experience matters most)
(3) Hopefully the new salary policy will attract more talent to the AIM ecosystem, such that (a) AIM would have less need to hire people who would otherwise found, and (b) more new founders are unlocked than AIM is capable of absorbing.
I really like this framework! Thank you!
It's very fair to be concerned that your donations might be doing harm -- I can relate! A bittersweet consolation might be that this is a risk that applies to basically every charitable intervention, including highly evidence-based global health and development interventions. Something that increases a woman's income or autonomy can put her at greater risk of domestic violence for example. Changing someone's life can have impacts on the local and macro-economy, on those impacted by their diet and consumption patterns etc. -- the world is complicated and the risk of doing harm instead of good is always there.
This isn't to say we shouldn't work really hard to understand and prevent such harm! Just that "no chance of harm" is not a realistic bar to aim for
"If there had been 50 studies which compared mortality between two global health intervention and overall results was unequivocal, we would probably conclude that there was no major difference between the two, rather than say we didn't have a clear answer and needed more research." -- True, but the goal of cage-free isn't reducing mortality, it's reducing suffering. Mortality is one possible (but deeply confounded) indicator of suffering we can look at. If, when doing so, we conclude that there is no major difference between mortality in caged and cage-free systems, this has little to no bearing on whether cage-free reduces suffering.
We vibecoded an app script to do it in Google Sheets at AIM, and there’s Guesstimate and the other one (I forget its name). So I agree that it’s easy to do this and people should do so more!
Got it, makes sense. I'm not sure it makes sense to think of these pain levels as discrete categories, but I think your point holds even if we're just using them to gesture at rough areas on a spectrum
“There are good reasons that some of the most rigorous organizations in the space (CG) have made cage-free a top priority and ex ante you should think it unlikely that they all converged without good reasons” — I agree, with the caveat that sometimes what looks like (A) converging opinions of a number of thoughtful actors is actually (B) a chain of deference where one actor has thought about it, and a second actor defers to them, and a third defers to the first two etc, with the nuance and uncertainty getting lost a bit more at every step in the chain. It can be hard to tell A and B apart from the outside
Oh right got it. Thank you. But if (I emphasize: IF) we thought cage-free was negative we could choose to not do that bit right? The sign of the overall portfolio doesn’t seem relevant to that decision
I agree with the other, secondary Aidan’s comment (I am the original and true Aidan).
A common journey with EA is going from (1) not thinking we can know whether charity is helping or that it makes a difference which charity you choose to (2) learning about EA and being thrilled to discover that we can know and some charities are excellent to (3) getting into the weeds of the empirical and ethical uncertainties around the first, 2nd and nth order effects of a certain cause area and becoming disillusioned and pivoting to another cause to (4) realising that every cause is fraught with uncertainty and starting to feel a bit jaded about charity to (5) accepting that the world is super uncertain but that the expected impact of the best bets we have is promising enough to motivate ongoing work on them (especially if we double down on generating more primary evidence and doing good M&E to make our uncertainty go down with time)
I hope we don’t lose you at the 4th step ❤️
(This is not to say that all causes are equally uncertain, or that it’s guaranteed that the best bets in any particular cause will be compelling enough for you)
I really appreciate this post and am also very excited to see more primary research. In addition to the uncertainty about how a given change in farming practices impacts welfare, I think whether or not those changes are actually occurring is highly uncertain, and I’d like to see a greater investment in M&E at animal orgs to validate this.
More primary research could be complementary to this, for example, better monitoring of welfare indicators on farms and/or at slaughter could allow us to see whether the welfare is actually improving, which requires both that the intervention is actually occurring and that it’s helping animals when it occurs.
I do wonder about our ability to measure harms like stress and fear though. I think focusing just on mortality or health conditions might lead us to make false conclusions about which farming practices are better for animals. Does anyone know anything about our capacity to measure psychological distress from deprivation of natural behaviors vs fear of violence for example? (the former being one that drives a significant amount of the improvement that cage-free brings according to WFI, the latter being one Amanda points to being absent and potentially outweighing the former)