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This is a linkpost for Brian Tomasik's posts on charity.

My Donation Recommendations

By Brian Tomasik

First published: 2014 Nov 02. Last nontrivial update: 2018 May 02.

Note from 2022 Jun 27: The details in this piece are slightly outdated. Maybe I'll update this page at some point, but for now, here's a quick summary of my current views.

In terms of maximizing expected suffering reduction over the long-run future, my top recommendation is the Center for Reducing Suffering (CRS), closely followed by the Center on Long-Term Risk (CLR). (I'm an advisor to both of them.) I think both of these organizations do important work, but CRS is more in need of funding currently.

CRS and CLR do research and movement building aiming to reduce risks of astronomical suffering in the far future. This kind of work can feel very abstract, and it's difficult to know if your impact is even net good on balance. Personally I prefer to also contribute some of my resources toward efforts that more concretely reduce suffering in the short run, to avoid feeling like I'm possibly wasting my life on excessive speculation. For this reason, I plan to donate my personal wealth over time toward charities that work mainly or exclusively on improving animal welfare. (I prefer welfare improvements over reducing meat consumption because the sign of the latter for wild-animal suffering is unclear.) The Humane Slaughter Association is my current favorite. A decent portion of the charities granted to by the EA Funds Animal Welfare Fund also do high-impact animal welfare work. I donate a bit to Animal Ethics as well.


This piece describes my views on a few charities. I explain what I like about each charity and what concerns me about it. Currently, my top charity recommendation for someone with values similar to mine is the Foundational Research Institute (an organization that I co-founded and volunteer for).

Spreading Google Grants with Caution about Counterfactuals

By Brian Tomasik

First published: 2014 Feb 04. Last nontrivial update: 2016 Nov 09.


If you find an effective charity, write to them to ask whether they use Google Grants, and if not, suggest they sign up. Google Grants offers the prospect of immense returns for a small amount of labor, although one needs to be careful about not competing with other effective organizations and choosing keywords that draw in new people rather than preaching to the choir.

Update (2015 Sep): Having used Google Grants for the last 1.5 years for several organizations, my conclusion is that the value of AdWords is modest. None of my organizations has found via AdWords a major donor or a promising future employee, even though our websites get high traffic volume from ads. Maybe part of the reason is that the best people don't click on ads much? Another reason is that the best people tend to be concentrated in dense social clusters, so that networking can be more effective.

The Haste Consideration, Revisited

By Brian Tomasik

First published: 2013 Feb 03. Last nontrivial update: 2018 Apr 19.


Internal rates of return for charity are high, but they may not be as high as they seem naively. Haste is important, but because long-term growth is logistic rather than exponential, it's less important than has been suggested by some. That said, if artificial general intelligence (AGI) comes soon and exponential growth does not level off too quickly, naive haste may still be roughly appropriate. There are other factors for and against haste that parallel donate-vs.-invest considerations.

Restating the summary in simpler language: Movements should saturate or at least show diminishing returns at some point, so that movement building sooner amounts to either just a few more years of the movement existing or only modest marginal increases in the movement's size. These impacts could still matter—they're just not as extreme as in a naive model in which, if it takes 2 years to create a hard-core altruist, then starting 2 years earlier doubles the long-term number of altruists.

Quantify with Care

By Brian Tomasik

First published: 2013 Feb 23. Last nontrivial update: 2016 May 20.


Quantification and metric optimization are powerful tools for reducing suffering, but they have to be used carefully. Many studies can be noisy, and results that seem counterintuitive may indeed be wrong because of sensitivity to experiment conditions, human error, measurement problems, or many other reasons. Sometimes you're looking at the wrong metric, and optimizing a metric blindly can be dangerous. Designing a robust set of metrics is actually a nontrivial undertaking that requires understanding the problem space, and sometimes it's more work than necessary. There can be a tendency to overemphasize statistics at the expense of insight and to use big samples when small ones would do. Finally, think twice about complex approaches that sound cool or impressive when you could instead use a dumb, simple solution.

Charity Cost-Effectiveness in an Uncertain World

29 August 2015 | by Brian Tomasik

First written: 28 Oct. 2013; last update: 4 Dec. 2015


Evaluating the effectiveness of our actions, or even just whether they're positive or negative by our values, is very difficult. One approach is to focus on clear, quantifiable metrics and assume that the larger, indirect considerations just kind of work out. Another way to deal with uncertainty is to focus on actions that seem likely to have generally positive effects across many scenarios, and often this approach amounts to meta-level activities like encouraging positive-sum institutions, philosophical inquiry, and effective altruism in general. When we consider flow-through effects of our actions, the seemingly vast gaps in cost-effectiveness among charities are humbled to more modest differences, and we begin to find more worth in the diversity of activities that different people are pursuing. Those who have abnormal values may be more wary of a general "promote wisdom" approach to shaping the future, but it seems plausible that all value systems will ultimately benefit in expectation from a more cooperative and reflective future populace.

Why Charities Usually Don't Differ Astronomically in Expected Cost-Effectiveness

[This post has been crossposted to the EA Forum.]

By Brian Tomasik

First published: 2014 Jan 05. Last nontrivial update: 2017 Sep 16.


I think some in the effective-altruism movement overestimate the extent to which charities differ in their expected marginal cost-effectiveness. This piece suggests a few reasons why we shouldn't expect most charities to differ by more than hundreds of times. In fact, I suspect many charities differ by at most ~10 to ~100 times, and within a given field, the multipliers are probably less than a factor of ~5. These multipliers may be positive or negative, i.e., some charities have negative expected net impact. I'm not claiming that charities don't differ significantly, nor that we shouldn't spend substantial resources finding good charities; indeed, I think both of those statements are true. However, I do hope to challenge black/white distinctions about effective/ineffective charities, so that effective altruists will see greater value in what many other people are doing in numerous places throughout society.





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Sorted by Click to highlight new comments since: Today at 10:02 AM

Tomasik's claim (emphasis mine)

I suspect many charities differ by at most ~10 to ~100 times, and within a given field, the multipliers are probably less than a factor of ~5.

reminded me of this (again emphasis mine) from Ben Todd's 80K article How much do solutions to social problems differ in their effectiveness? A collection of all the studies we could find

Overall, my guess is that, in an at least somewhat data-rich area, using data to identify the best interventions can perhaps boost your impact in the area by 3–10 times compared to picking randomly, depending on the quality of your data.

This is still a big boost, and hugely underappreciated by the world at large. However, it’s far less than I’ve heard some people in the effective altruism community claim.

In addition, there are downsides to being data-driven in this way — by insisting on a data-driven approach, you might be ruling out many of the interventions in the tail (which are often hard to measure, and so will be missing). This is why we advocate for first aiming to take a ‘hits-based’ approach, rather than a data-driven one.

"Hits-based rather than data-driven" is a pretty thought-provoking corrective to me, as I'm maybe biased by my background having worked in data-rich environments my whole career.

Executive summary: Brian Tomasik discusses his top recommended charities, the value of spreading Google Grants, factors relating to the haste consideration for movement growth, issues around quantification and metrics, evaluating charities amidst uncertainty, and why charities may not differ astronomically in cost-effectiveness.

Key points:

  1. Tomasik currently recommends the Center for Reducing Suffering, the Center on Long-Term Risk, the Humane Slaughter Association, and some EA Funds charities.
  2. Google Grants offers high returns for little effort but requires care to avoid competing with other organizations or just preaching to the choir.
  3. Haste has diminishing returns so is less crucial than sometimes thought, though it still matters, especially if AI comes soon.
  4. Quantification is useful but metrics can be misused or overemphasized relative to judgment and simplicity.
  5. Amidst uncertainty, general promotion of cooperation and reflection may be safest, though abnormal values warrant more caution.
  6. Charity cost-effectiveness likely does not differ astronomically due to uncertainty, indirect effects, and regression to the mean.



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