Co-founder of Charity Science, a nonprofit that runs multiple projects, including Charity Science Health (a Givewell incubated charity) and Charity Entrepreneurship (a program to help new charities get founded).
Joey
Karma: 5,942
Five New EA Charities with High Potential for Impact
Equally or more focused on doing good but less involved with the EA movement. Broadly I am less sold that engaging with the EA movement is the best way to increase knowledge or impact. This is due to a bit of an intellectual slowdown in EA, with fewer concepts being generated that connect to impact and a bit of perceived hostility towards near-term causes (which I think are the most impactful).
Hey Charles, we don’t prioritize long termist projects as we do not think they are the highest impact (for epistemic not ethical reasons). This view is pretty common in EA, but most people who hold this perspective do not engage much on the EA forum. In the future we might write more on it.
We have recommended meta charities in the past (e.g. animal careers) and expect to recommend more in the future. There are some people considering a long-term/AI focused incubator, so this might be a project that happens at some point.
Sadly don’t have time to go into much depth on this, but we strongly recommend it to all charities that run through our CE program (including all the research orgs) and create a ToC for each idea we research.
Announcement: applications for the 2020 Charity Entrepreneurship Incubation Program are now open!
Comparing Four Cause Areas for Founding New Charities
Announcement: early applications for Charity Entrepreneurship’s 2020 Incubation Program are now open!
Here are a few different areas that look promising. Some of these are taken from other organizations’ lists of promising areas, but I expect more research on each of them to be high expected value.
Donors solely focused on high-income country problems.
Mental health research (that could help both high and low income countries).
Alcohol control
Sugar control
Salt control
Trans-fats control
Air pollution regulation
Metascience
Medical research
Lifestyle changes including “nudges” (e.g. more exercise, shorter commutes, behaviour, education)
Mindfulness education
Sleep quality improvement
Donors focused on animal welfare.
Wild animal suffering (non-meta, non-habitat destruction) interventions
Animal governmental policy, particularly in locations outside of the USA and EU.
Treat disease that affects wild animals
Banning live bait fish
Transport and slaughter of turkeys
Pre-hatch sexing
Brexit related preservation of animal policy
Donors focused on improving the welfare of the current generation of humans.
Pain relief in poor countries
Contraceptives
Tobacco control
Lead paint regulation
Road traffic safety
Micronutrient fortification and biofortification
Sleep quality improvement
Immigration reform
Mosquito gene drives, advocacy, and research
Voluntary male circumcision
Research to increase crop yields
Cause X Guide
Slight correction: The Charity Entrepreneurship program will be based in London, UK this year.
When I was writing this, I was mostly comparing it to other highly time consuming activism (e.g. many people are getting a degree hoping it will help them acquire an EA job). In terms of being the optimal thing for EA organizations to look for, I do not really have a view on that. I was more so hoping to level the understanding between people who have a pretty good sense that this sort of information is what you need, and people who might think that this would be worth far less than, say, a degree from a prestigious university.
A guide to improving your odds at getting a job in EA
Ok given multiple people think this is off I have changed it to 3 hours to account for variation in application time.
My sense is they already had a CV that required very minimal customization and spent almost all the time on the cover letter.
It came from asking ~4 successful employees who where hired
The following is a rough breakdown of the percentage of people who were not asked to move on to the next round in the Charity Science hiring process. These numbers assume one counterfactual hour of preparation for each interview and no preparation time outside of the given time limit for test tasks.
~3* hour invested (50%) - Cover letter/resume
~5 hours invested (20%) - Interview 1
~10 hours invested (15%) - Test task 1
~12 hours invested (5%) - Interview 2
~17 hours invested (5%) - Test task 2
~337 hours invested (2.5%) - paid 2-month work trial
Hired (2.5%)
So, 95% of those not hired spend 17 hours or less, 85% spend 14 hours or less, and 70% spend 5 hours or less.*changed from 1 hour to 3 hours based on comments
Hey Abraham,
The endline goal of any piece of evaluation criteria is to be able to be used to best predict “good done”. I broadly agree that one criteria factor is unlikely to rule in or out an intervention fully (including limiting factor—it was one of four in our system). If we know a criteria that was that powerful there would be no need for complex evaluation.
Although limiting factor is not a pure hard limit I do not think this changes its usefulness much; an intervention might be low evidence, and in theory multiple RCTs could be done to improve this, but in practice if there is say a limiting factor on funding (such that multiple RCTs could not be funded) the intervention might be indefinitely low evidenced even if in theory evidence is not an independent of movement factor. It seems fairly clear that all things being equal running an intervention will be easier than running an equivalent intervention that also requires you to build a field of talent or otherwise work on a limiting factor.
In principle I think this could be put into a more numerical form (e.g. included in CEA), but I think in practice this has not been done. Historically maybe the closest is different levels of funding gaps that Givewell has put for there top charities, but that is mostly considering a single possible limiting factor (funding). I would love to see more models on limiting factor and think it would be a natural next step in the current EA talent vs funding conversations.A different way to think about this question is do we think problem scale or limiting factor are better predictors of areas where the most good can be done? I pretty strongly disagree that problem scale is more important than the limiting factor that will hit an intervention. Theoretically scale of the problem is a harder limit but that doesn’t really matter if in practice an intervention is never capped by it. We ended up looking at quite a number of charities to consider what was stopping them (including GiveWell and ACE recommendations) and none of them seemed to be capped by problem scale, they had all been stopped by other limiting factors far before that became an issue (for example, with AMF it was funding and logistical bottlenecks not the number of people with malaria). I think this is even true for the specific case of wild suffering interventions. The absolute number of bugs does not matter much when considering ethical pest control so much as the density per hectare of field or the available funding for a humane insecticides charity. You could imagine a world where the bug populations of colder locations (such as Canada and Russia) where close to 0 and it would do very little to affect the estimated good done- broadly due to having a ton of work to do in warmer locations before one would expand to Canada and likely hitting many limiting factors before expanding that far. How soon these problems hit would be more predictive of impact than if there were twice or half as many bugs in the world as there are now.
I think historical evidence like “if this was not done X would not never have happened” is not a very strong argument unless some research is done systematically and compares both the hits and misses that occured (e.g. there where a lot of issues that were attempted to be founded but never got traction at that same point in time). To take a more clear example you could look a friend who won the lottery, and although clearly he benefited from his ticket it still would have been the wrong call from an expected value perspective to buy it, and certainly would not suggest you should buy a lottery ticket we have to be careful of survivorship bias. Mainly we are looking at factors that are predictive of something having the most impact and singular examples do not describe much about field building vs making quicker progress on a more established field. Although I would be really interested in more systematic research in this area.
Good idea, I added CE to the first use of “we”.
Hey Ramiro and Thomas,
Thanks for your engagement with this system. I think in general our system has lots of room for improvement—we are in fact working on refining it right now. However, I am pretty strongly in favor of having evaluation systems even if the numbers are not based on all the data we would like them to be or even if they come to surprising results.
Cross species comparison is of course very complex when it comes to welfare. Some factors are fairly easy to measure across species (such as death rates) while others are much more difficult (diseases rates are a good example of where it’s hard to find good data for wild animals). I can imagine researchers coming to different conclusions given the same initial data.
It’s worth underlining that our system does not aim to evaluate the moral weight of a given species, but merely to assess a plausible state of welfare. (Thomas: this would be one caveat to add when sharing.) In regards to moral weight (e.g. what moral weight do we accord a honey bee relative to a chicken etc.) – that is not really covered by our system. We included the estimates of probability of consciousness per Open Phil’s and Rethink Priorities’ reports on the subject, but the moral weight of conscious human and non-human animals is a heavily debated topic that the system does not go into. Generally I recommend Rethink Priorities’ work on the subject.
In regards to welfare, I think it’s conceptually possible that e.g. a well treated pet dog in a happy family may be happier and their life more positive than a prisoner in a North Korean concentration camp. This may seem unintuitive, but I also find the inverse conclusion unintuitive. As mentioned above, that doesn’t mean that we should be prioritizing our efforts on improving the welfare of pet dogs vs. humans in North Korea. Prioritizing between different species is a complex issue, of which welfare comparisons like this index may form one facet without being the only tool we use.
To cover some of the specific claims.
- Generally, I think there is some confusion here between the species having control vs the individual. For example, North Korea as a country has a very high level of control over their environment, and can shape it dramatically more than a tribe of chimps can. However, each individual in North Korea has extremely limited personal control over their life – often having less free time and less scope for action than a wild chimp would practically (due to the constraints of the political regime) if not theoretically (given humanity’s capabilities as a species).
- We are not evaluating hunter gatherers, but people in an average low-income country. Life satisfaction measures show that in some countries, self-evaluated levels of subjective well-being are low. (Some academics even think that this subjective well-being could be lower than those of hunter gatherer societies.)
- Humanity has indeed spent a great deal more on diagnosing humans than chimps. However, there is some data on health that is comparable, particularly when it comes to issues that are clearer to observe such as physical disability.
- There is in fact some research on hunger and malnutrition in wild chimps, so this was not based on intuitions but on best estimates of primatologists. Malnourishment in chimps can be measured in some similar ways to human malnourishment, e.g. stunting of growth. I do think you’re right that concerns with unsafe drinking water could be factored into the disease category instead of the thirst one.
I would be keen for more research to be done on this topic but I would expect it to take a few hours of research into chimp welfare and a decent amount of research into human welfare to get a stronger sense than our reports currently offer. I think these sorts of issues are worth thinking about and we would like to see more research being done using such a system that aims to evaluate and compare the welfare of different species. Thank you again for engaging with the system—we’ll bear your comments in mind as we work on improvements.