Their cost effectiveness was lower than that of their âcompetitorâ because their competitor paid themselves a lower salary. This is a race to the bottom that is unhealthy for the movement.
There are many EAs would would like to get a job at an EA org, and lower salaries means that more jobs can be offered. So I think EA âunemploymentâ is a bigger problem for the movement than the people who do have EAs jobs not making enough money.
It would attract talent that otherwise wouldâve been inaccessible because that talent wouldnât have been willing to take as big of a sacrifice.
Yes, but I generally think there is talent available in the EA community.
2. It would allow less privileged groups to join the charity world that otherwise just wouldnât have the means to take paycuts like this.
Most salaries at EA orgs are in the top couple percent of the world, so I donât think this is a big issue.
3. It would give employees a tangible measure to estimate how much impact they are having with their job.
Most employees already know the market rate, so they can subtract. And I think most orgs do appreciate their employees for working for less than market rate. But I could see it helping with getting credit for GWWC.
A disadvantage of starting with market rate is that the person who wouldâve accepted the NGO rate might on average pay themselves more because they would more consciously have to give up money. They means a combination of more donor money required and more EA âunemploymentâ, which I think would reduce effectiveness overall.
A disadvantage of starting with market rate is that the person who wouldâve accepted the NGO rate might on average pay themselves more because they would more consciously have to give up money.
This is implying we are right now tricking people into giving up more than they consciously would. Iâm not sure thatâs what we would want as a movement.
Most salaries at EA orgs are in the top couple percent of the world, so I donât think this is a big issue.
I think this might vary heavily depending on the focus area. In AI for sure, not sure about the others.
There are many EAs would would like to get a job at an EA org, and lower salaries means that more jobs can be offered. So I think EA âunemploymentâ is a bigger problem for the movement than the people who do have EAs jobs not making enough money.
Iâm aware of the EA unemployment but Iâm not sure if we should optimize for EAs working in EA orgs. Shouldnât the best talent or fit win? Especially for hard-to-fill roles like biorisk researchers, AI alignment people, a GiveDirectly country operation manager role, etc. Of course, value alignment shoudl play a part in assessing job match, but Iâm not sure willingness to take a low salary is the right selector.
Either way, all these points are downstream of the main point Iâm trying to make: We should take market rate equivalents in cost effectivness calculations so we donât overpromise impact to donors. We can do this and then still decide to only accept candidates that take a 50% pay cut.
>A disadvantage of starting with market rate is that the person who wouldâve accepted >the NGO rate might on average pay themselves more because they would more >consciously have to give up money.
This is implying we are right now tricking people into giving up more than they consciously would. Iâm not sure thatâs what we would want as a movement.
I donât think so-thereâs an analogy here with opt in versus opt out. You could say that people have a certain preference to be an organ donor and that whether it is opt in or opt out, you should get the same percent of participation of being an organ donor. However, we find that in reality, whether the system is opt in or opt out has a huge impact on the actual participation rate. This is similar for retirement programs.
I think this might vary heavily depending on the focus area. In AI for sure, not sure about the others.
Claude says 98th percentile salary globally is USD48k, and it estimates the median at AI-aligned orgs to be $65k for animals, $85k for global health, meta $85k and AI safety $115k.
Iâm aware of the EA unemployment but Iâm not sure if we should optimize for EAs working in EA orgs. Shouldnât the best talent or fit win? Especially for hard-to-fill roles like biorisk researchers, AI alignment people, a GiveDirectly country operation manager role, etc. Of course, value alignment shoudl play a part in assessing job match, but Iâm not sure willingness to take a low salary is the right selector.
I agree that we should be maximizing overall effectiveness, and that reducing EA âunemploymentâ should not be a primary goal. However, I do think that there are a lot of well-qualified EAs who have not been able to get an EA job (see here for links). I think there are social pressures to have EA wages not lower than other nonprofits. As evidenced by some EAsâ donating patterns, they are willing to accept lower wages than most. So I think that total effectiveness would be higher with lower wages. Of course it does not apply in all cases.
Either way, all these points are downstream of the main point Iâm trying to make: We should take market rate equivalents in cost effectivness calculations so we donât overpromise impact to donors. We can do this and then still decide to only accept candidates that take a 50% pay cut.
I definitely agree with the point that we should be recognizing the contribution of people who work for less money, including volunteers. Unlike Shapely values, counterfactuals can add up to more than 100%. This might be better in the other comment thread about volunteers, but here goes anyway. Letâs say we have charity A that does one unit of impact per employee, and charity B that does one unit of impact per employee but each employee also manages volunteers that produce another unit of impact. I think that the counterfactual impact of the donor by funding the salary of the employee at charity B is two units, because without the donor, you would not get any impact. Then I think the counterfactual impact of the volunteers is one unit (because it wouldnât happen without them). Letâs assume the employee is paid at market rate and replaceable for this thought experiment. So then we have two units of impact but the counterfactual impact is three units. So obviously Shapely values that must add to 100% you canât give all the impact to the donor. And you can easily come up with more complicated scenarios where this will not work out as cleanly. But I do think itâs possible that using volunteers (or lower salaries) can increase the counterfactual impact of the donor.
Great opt-in vs opt-out framing, that snarky comment of mine about tricking people was written too fast!
About that example: I think you meant to write âat charity Bâ instead of âat charity Aâ? * Charity A: 1 employees at market rate, one unit of impact > 1 impact for donor * Charity B: 1 employees at market rate, one unit of impact + 1 volunteers with 1 impact > 2 impact for donor
I think that the donor should not have â2 counterfactual impactâ in this case. But maybe I am misunderstanding things.
Letâs play with some more examples * Charity C: 1 employee and 10000 volunteers, 10001 impact total. Should the donor really get 10001 impact? To me that feels really off
* Charity D: The employee also becomes a volunteer but does the same job. In a way the employee is âdonatingâ their salary and becomes the donor. Should the employee now get â2 impactsâ? That again feels off? Are they somehow better than the other volunteer?
* Charity E: 100 donors, all donating $1. Itâs a blind kickstarter campaign and the charity can only do the intervention if they raise 100, otherwise money back, but the donors donât know how many others already donated, so order doesnât matter. In a way each donor should get the full âcounterfactualâ impact because without each individual donor the fundraise wouldâve failed. But again attributing the same full impact 100 times feels wrong.
About that example: I think you meant to write âat charity Bâ instead of âat charity Aâ?
Yesâthank youâfixed!
* Charity C: 1 employee and 10000 volunteers, 10001 impact total. Should the donor really get 10001 impact? To me that feels really off
Very unlikely to be the case in the real world, but if the donor makes the whole chain of events happen, then I think that is the counterfactual impact.
* Charity D: The employee also becomes a volunteer but does the same job. In a way the employee is âdonatingâ their salary and becomes the donor. Should the employee now get â2 impactsâ? That again feels off? Are they somehow better than the other volunteer?
Again, if without that person, there would be no impact, I think thatâs the counterfactual. In general, a volunteer who could manage other volunteers I think would be more valuable.
* Charity E: 100 donors, all donating $1. Itâs a blind kickstarter campaign and the charity can only do the intervention if they raise 100, otherwise money back, but the donors donât know how many others already donated, so order doesnât matter. In a way each donor should get the full âcounterfactualâ impact because without each individual donor the fundraise wouldâve failed. But again attributing the same full impact 100 times feels wrong.
Yeahâan even more extreme case would be an election with 100,000,001 votes versus 100,000,000 votesâwould all 100,000,001 people get to claim they cast the deciding vote for the election? Perhaps someone who has thought more about this wants to weigh in? @aaronhamlin ?
There are many EAs would would like to get a job at an EA org, and lower salaries means that more jobs can be offered. So I think EA âunemploymentâ is a bigger problem for the movement than the people who do have EAs jobs not making enough money.
Yes, but I generally think there is talent available in the EA community.
Most salaries at EA orgs are in the top couple percent of the world, so I donât think this is a big issue.
Most employees already know the market rate, so they can subtract. And I think most orgs do appreciate their employees for working for less than market rate. But I could see it helping with getting credit for GWWC.
A disadvantage of starting with market rate is that the person who wouldâve accepted the NGO rate might on average pay themselves more because they would more consciously have to give up money. They means a combination of more donor money required and more EA âunemploymentâ, which I think would reduce effectiveness overall.
This is implying we are right now tricking people into giving up more than they consciously would. Iâm not sure thatâs what we would want as a movement.
I think this might vary heavily depending on the focus area. In AI for sure, not sure about the others.
Iâm aware of the EA unemployment but Iâm not sure if we should optimize for EAs working in EA orgs. Shouldnât the best talent or fit win? Especially for hard-to-fill roles like biorisk researchers, AI alignment people, a GiveDirectly country operation manager role, etc. Of course, value alignment shoudl play a part in assessing job match, but Iâm not sure willingness to take a low salary is the right selector.
Either way, all these points are downstream of the main point Iâm trying to make: We should take market rate equivalents in cost effectivness calculations so we donât overpromise impact to donors. We can do this and then still decide to only accept candidates that take a 50% pay cut.
I donât think so-thereâs an analogy here with opt in versus opt out. You could say that people have a certain preference to be an organ donor and that whether it is opt in or opt out, you should get the same percent of participation of being an organ donor. However, we find that in reality, whether the system is opt in or opt out has a huge impact on the actual participation rate. This is similar for retirement programs.
Claude says 98th percentile salary globally is USD48k, and it estimates the median at AI-aligned orgs to be $65k for animals, $85k for global health, meta $85k and AI safety $115k.
I agree that we should be maximizing overall effectiveness, and that reducing EA âunemploymentâ should not be a primary goal. However, I do think that there are a lot of well-qualified EAs who have not been able to get an EA job (see here for links). I think there are social pressures to have EA wages not lower than other nonprofits. As evidenced by some EAsâ donating patterns, they are willing to accept lower wages than most. So I think that total effectiveness would be higher with lower wages. Of course it does not apply in all cases.
I definitely agree with the point that we should be recognizing the contribution of people who work for less money, including volunteers. Unlike Shapely values, counterfactuals can add up to more than 100%. This might be better in the other comment thread about volunteers, but here goes anyway. Letâs say we have charity A that does one unit of impact per employee, and charity B that does one unit of impact per employee but each employee also manages volunteers that produce another unit of impact. I think that the counterfactual impact of the donor by funding the salary of the employee at charity B is two units, because without the donor, you would not get any impact. Then I think the counterfactual impact of the volunteers is one unit (because it wouldnât happen without them). Letâs assume the employee is paid at market rate and replaceable for this thought experiment. So then we have two units of impact but the counterfactual impact is three units. So obviously Shapely values that must add to 100% you canât give all the impact to the donor. And you can easily come up with more complicated scenarios where this will not work out as cleanly. But I do think itâs possible that using volunteers (or lower salaries) can increase the counterfactual impact of the donor.
Edited to switch to charity B.
Great opt-in vs opt-out framing, that snarky comment of mine about tricking people was written too fast!
About that example: I think you meant to write âat charity Bâ instead of âat charity Aâ?
* Charity A: 1 employees at market rate, one unit of impact > 1 impact for donor
* Charity B: 1 employees at market rate, one unit of impact + 1 volunteers with 1 impact > 2 impact for donor
I think that the donor should not have â2 counterfactual impactâ in this case. But maybe I am misunderstanding things.
Letâs play with some more examples
* Charity C: 1 employee and 10000 volunteers, 10001 impact total. Should the donor really get 10001 impact? To me that feels really off
* Charity D: The employee also becomes a volunteer but does the same job. In a way the employee is âdonatingâ their salary and becomes the donor. Should the employee now get â2 impactsâ? That again feels off? Are they somehow better than the other volunteer?
* Charity E: 100 donors, all donating $1. Itâs a blind kickstarter campaign and the charity can only do the intervention if they raise 100, otherwise money back, but the donors donât know how many others already donated, so order doesnât matter. In a way each donor should get the full âcounterfactualâ impact because without each individual donor the fundraise wouldâve failed. But again attributing the same full impact 100 times feels wrong.
Yesâthank youâfixed!
Very unlikely to be the case in the real world, but if the donor makes the whole chain of events happen, then I think that is the counterfactual impact.
Again, if without that person, there would be no impact, I think thatâs the counterfactual. In general, a volunteer who could manage other volunteers I think would be more valuable.
Yeahâan even more extreme case would be an election with 100,000,001 votes versus 100,000,000 votesâwould all 100,000,001 people get to claim they cast the deciding vote for the election? Perhaps someone who has thought more about this wants to weigh in? @aaronhamlin ?