There’s quite a few opportunities I see from looking around in EA. I am doing direct technical work for EA right now.
EA CoLabs
EA CoLabs itself can be framed as a technical problem. It’s the problem of optimally matching different skillsets to different projects to maximise utility. You could definitely tackle it from a fun technical perspective (say, using the Hungarian Algorithm for matching, and using the Australian Skills Classification to describe skills). These however are just my ideas. I may be currently too busy with other things to properly investigate whether this is feasible.
Certificates of Impact and EA Economies
There are a lot of interesting ideas in creating economies around EA. For instance, having people sell products where all proceeds go to charity. I have a friend who wishes to look into using technologies such as blockchain to track coins that can be used to purchase good where the profits end up to Effective Charities.
Improving Infrastructure around Cost Effectiveness Analysis
This is what I’m currently doing as direct work. Cost Effectiveness Analysis are not really done to a very high quality in EA spaces as yet, and it would be nice to see more analysis so that we can make more informed decisions. I see this as a major tooling opportunity, as the state of the art in this area uses excel and a lot of time. This may include improving on technologies like Guesstimate, or building entirely new technologies.
Improving Infrastructure around epistemics and forecasting
The next area I would highlight is that there needs to be better evaluations of things like Cost Effectiveness Analysis, or really any other important calculations or predictions. These evaluations often aren’t really done, and I would love to see proper evaluations say for parameters in GiveWell’s Cost Effectiveness Analysis.
If you are interested in any of these. Please reply/get in contact.
For Improving Infrastructure around Cost Effectiveness Analysis, my current project is pedant.
Pedant is a math DSL that’s designed to make it easier to write cost effectiveness analysis. It checks the calculations for things like dimensional violations, and hopefully in the future allows you to calculate with uncertainties and explore cost effectiveness calculations more graphically.
I wouldn’t say that there are people who are asking for cost effectiveness analysis, and more that they simply aren’t done or are of low quality to large amounts of EA causes. For instance, even GiveWell’s work that we consider to be the gold standard does not properly account for uncertainty in parameters (although Cole Haus has done so in the forum), there is controversy around the accuracy of ALLFED’s guesstimate Cost Effectiveness Model, which may be systematically optimistic about their parameters, and these are some of the best ones out there! I don’t believe ACE uses explicit cost effectiveness calculations, let alone smaller EA organisations. In conversions with Ozzie and Michael Aird I believe that they seem to share a similar sentiment.
I mainly just assumed that this problem could be because these calculations are quite difficult to do, take a lot of time, and can be very difficult to get right. So as a developer I just thought tooling. I’m not particularly creative.
I would be interested in collaborators. Help I would need includes:
Actual coding of pedant. Mainly you would need to be familiar with Haskell to the extent that you can code basic parsers.
Feedback on development. I’m always on the lookout for people who can tell me when I’m wrong and should work on something else. I’ve currently got two sources of feedback. I would be more than willing to have a third.
Testing and usage. I’d love to see someone use pedant to do a variety of cost effectiveness analysis just to see what types of features are most needed in the language. I’ve currently got a CEA for GiveDirectly and the Against Malaria Foundation, and would appreciate help on writing the rest of GiveWell’s charities out, and maybe even other calculations such as ALLFED’s CEAs or Nuno’s Shallow Evaluations of Longtermist Organizations. You need a lot of patience to do this, it does take a while, and you are doing really simple transformation from one format to another.
Documentation and recommendations. It would be lovely to get a list of recommendations and best practices for writing cost effectiveness calculations based on what say GiveWell has done. Currently, the only documentation for pedant is the README file on the main page.
Really, if you or anyone else is interested, probably best to just contact me directly.
For Improving Infrastructure around epistemics and forecasting, Ozzie or Nuno would likely be the best to answer this, so here I’m just trying to put myself in their mind. These ideas are a mixture of mine + a discussion with Ozzie.
I would say a clear opportunity would be to investigate looking into writing prediction functions, rather than just predictions. Say for instance “If SpaceX has a press release about an innovation to be released before 2025, then I estimate SpaceX to become a trillion dollar company 5 years earlier”. Having such a fidelity makes it possible to understand the best forecasting techniques better and aids in computer systems being able to answer these types of questions. As for as I know, this doesn’t exist.
As a side note, I think this type of forecasting platform would be awesome for policy evaluation. “If this policy is implemented in X way I predict that the policy will create a decrease in the unemployment rate by Y%”. The applications of the proper application of this idea are endless.
Another would be creating a platform that allows you to properly calibrate parameters for a Cost Effectiveness Calculation using forecasting, or evaluate outcomes of business decisions using forecasting.
I’m not a pro in this area, but that’s currently what I see.
“having people sell products where all proceeds go to charity” is different from simply earning to give as it uses this fact to market to a buyer. The idea is that I may be more willing to purchase a second hand book from someone else if I know that the proceeds go to an effective charity (although I find that this is a surprisingly weak motivator, in my experience people don’t purchase things even if they know the money goes to an effective charity...).
I run a bookstore to this end that is currently not that successful, that I really want to see become a larger thing. Although this is likely mainly because I’m not that good at running shopify stores.
There’s quite a few opportunities I see from looking around in EA. I am doing direct technical work for EA right now.
EA CoLabs
EA CoLabs itself can be framed as a technical problem. It’s the problem of optimally matching different skillsets to different projects to maximise utility. You could definitely tackle it from a fun technical perspective (say, using the Hungarian Algorithm for matching, and using the Australian Skills Classification to describe skills). These however are just my ideas. I may be currently too busy with other things to properly investigate whether this is feasible.
Certificates of Impact and EA Economies
There are a lot of interesting ideas in creating economies around EA. For instance, having people sell products where all proceeds go to charity. I have a friend who wishes to look into using technologies such as blockchain to track coins that can be used to purchase good where the profits end up to Effective Charities.
Improving Infrastructure around Cost Effectiveness Analysis
This is what I’m currently doing as direct work. Cost Effectiveness Analysis are not really done to a very high quality in EA spaces as yet, and it would be nice to see more analysis so that we can make more informed decisions. I see this as a major tooling opportunity, as the state of the art in this area uses excel and a lot of time. This may include improving on technologies like Guesstimate, or building entirely new technologies.
Improving Infrastructure around epistemics and forecasting
The next area I would highlight is that there needs to be better evaluations of things like Cost Effectiveness Analysis, or really any other important calculations or predictions. These evaluations often aren’t really done, and I would love to see proper evaluations say for parameters in GiveWell’s Cost Effectiveness Analysis.
If you are interested in any of these. Please reply/get in contact.
(Strong upvote!) (Feel free to split up your reply into separate comments if you want)
EA Colabs
I’m part of the team there and I have a lot of thoughts around it, perhaps commenting here wouldn’t be the best place
“having people sell products where all proceeds go to charity” / “the profits end up to Effective Charities”
How is this different from earning to give? (Or founders’ pledge)
Improving Infrastructure around Cost Effectiveness Analysis
Hearing things like this is why I posted this in the first place!! :D :D
Could you tell me much more? Who has these needs? What do they look like?
Would you like collaborators? (And if so, do you have some bar for their skill?
Improving Infrastructure around epistemics and forecasting
Same thing! Do you know of needs here?
For Improving Infrastructure around Cost Effectiveness Analysis, my current project is pedant.
Pedant is a math DSL that’s designed to make it easier to write cost effectiveness analysis. It checks the calculations for things like dimensional violations, and hopefully in the future allows you to calculate with uncertainties and explore cost effectiveness calculations more graphically.
I wouldn’t say that there are people who are asking for cost effectiveness analysis, and more that they simply aren’t done or are of low quality to large amounts of EA causes. For instance, even GiveWell’s work that we consider to be the gold standard does not properly account for uncertainty in parameters (although Cole Haus has done so in the forum), there is controversy around the accuracy of ALLFED’s guesstimate Cost Effectiveness Model, which may be systematically optimistic about their parameters, and these are some of the best ones out there! I don’t believe ACE uses explicit cost effectiveness calculations, let alone smaller EA organisations. In conversions with Ozzie and Michael Aird I believe that they seem to share a similar sentiment.
I mainly just assumed that this problem could be because these calculations are quite difficult to do, take a lot of time, and can be very difficult to get right. So as a developer I just thought tooling. I’m not particularly creative.
I would be interested in collaborators. Help I would need includes:
Actual coding of pedant. Mainly you would need to be familiar with Haskell to the extent that you can code basic parsers.
Feedback on development. I’m always on the lookout for people who can tell me when I’m wrong and should work on something else. I’ve currently got two sources of feedback. I would be more than willing to have a third.
Testing and usage. I’d love to see someone use pedant to do a variety of cost effectiveness analysis just to see what types of features are most needed in the language. I’ve currently got a CEA for GiveDirectly and the Against Malaria Foundation, and would appreciate help on writing the rest of GiveWell’s charities out, and maybe even other calculations such as ALLFED’s CEAs or Nuno’s Shallow Evaluations of Longtermist Organizations. You need a lot of patience to do this, it does take a while, and you are doing really simple transformation from one format to another.
Documentation and recommendations. It would be lovely to get a list of recommendations and best practices for writing cost effectiveness calculations based on what say GiveWell has done. Currently, the only documentation for pedant is the README file on the main page.
Really, if you or anyone else is interested, probably best to just contact me directly.
For Improving Infrastructure around epistemics and forecasting, Ozzie or Nuno would likely be the best to answer this, so here I’m just trying to put myself in their mind. These ideas are a mixture of mine + a discussion with Ozzie.
I would say a clear opportunity would be to investigate looking into writing prediction functions, rather than just predictions. Say for instance “If SpaceX has a press release about an innovation to be released before 2025, then I estimate SpaceX to become a trillion dollar company 5 years earlier”. Having such a fidelity makes it possible to understand the best forecasting techniques better and aids in computer systems being able to answer these types of questions. As for as I know, this doesn’t exist.
As a side note, I think this type of forecasting platform would be awesome for policy evaluation. “If this policy is implemented in X way I predict that the policy will create a decrease in the unemployment rate by Y%”. The applications of the proper application of this idea are endless.
Another would be creating a platform that allows you to properly calibrate parameters for a Cost Effectiveness Calculation using forecasting, or evaluate outcomes of business decisions using forecasting.
I’m not a pro in this area, but that’s currently what I see.
“having people sell products where all proceeds go to charity” is different from simply earning to give as it uses this fact to market to a buyer. The idea is that I may be more willing to purchase a second hand book from someone else if I know that the proceeds go to an effective charity (although I find that this is a surprisingly weak motivator, in my experience people don’t purchase things even if they know the money goes to an effective charity...).
I run a bookstore to this end that is currently not that successful, that I really want to see become a larger thing. Although this is likely mainly because I’m not that good at running shopify stores.
https://altruisticbook.net/
I have a friend who’s interested in much more ambitious ideas than this.