The Open Philanthropy Blog

Open Philanthropy’s ability to give effectively to the world’s most important and neglected causes hinges on the collective strength and expertise of our team. As such, we’ve thought extensively about how we can identify those who could most meaningfully contribute to Open Philanthropy’s mission, and how we can craft a recruitment process that encourages them to apply.

Recruiting Manager Anya Hunt sat down with Communications Officer Michael Levine to talk about Open Philanthropy’s approach to recruiting, the role of work tests in the application process, and measures we are taking to diversify our pipeline and attract talent from different communities. The questions and answers have been edited lightly for clarity.

Generally speaking, how does Open Philanthropy approach the recruitment process?

There are parallels to the way we approach grantmaking. Each hire is an investment — we’re making a bet that this person will help Open Phil more effectively carry out our mission. In both cases, we’re trying to be evidence-based where we can, but we’re also trying to minimize bureaucracy. We try to hold ourselves to rigorous standards of decision-making, accounting for our biases wherever possible. We can only be as effective as the people we hire. So we’re willing to invest an unusual amount of time and energy into sourcing and vetting candidates.

How does that mindset impact the recruiting process?

Mainly, it causes us to put work tests at the center of the process. After some basic screening, the first thing candidates do, typically, before we interview them, before anything else happens, is to take at least one work test, and we’ll pay them an honorarium to complete it. Then we evaluate it blind and generally admit people to the next round only if they meet a certain preset standard. This results in an unusually long process — that’s both an upside and a downside. It’s a downside for the obvious reasons, but it’s an upside because we think making a hire, and accepting an offer, is a really important decision on both our end and the candidate’s. Because onboarding new staff can be very costly to both us and the new hire, we aim to be highly confident in every offer we make (though of course we do still make mistakes).

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We believe that every life has equal value — and that philanthropic dollars can go particularly far by helping those who are living in poverty by global standards. Currently, many of the best giving opportunities we’ve found in the Global Health and Development focus area are recommended by GiveWell, a nonprofit dedicated to finding outstanding giving opportunities and publishing its full analysis to help donors decide where to give. (Learn more about our relationship with GiveWell here.)

GiveWell recently announced its recommendations for giving, a list that focuses on programs with a strong track record and excellent cost-effectiveness, can use additional funding to expand their core programs, and are exceptionally transparent. We have allocated an additional $100 million for GiveWell top charities, GiveWell standout charities, and GiveWell Incubation Grants in the year-end period (beyond what we’ve already granted to GiveWell-recommended charities earlier this year).

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When the Soviet Union began to fracture in 1991, the world was forced to reckon with the first collapse of a nuclear superpower in history.1 The USSR was home to more than 27,000 nuclear weapons, more than one million citizens working at nuclear facilities, and over 600 metric tons of nuclear fissile materials.2 It seemed inevitable that some of these weapons, experts, and materials would end up in terrorist cells or hostile states,3 especially given a series of recent failed attempts at non-proliferation cooperation between the US and the USSR.

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Last year, the year before, the year before that, the year before that, and the year before that, we published a set of suggestions for individual donors looking for organizations to support. This year, we are repeating the practice and publishing updated suggestions from Open Philanthropy program staff who chose to provide them.

Similar caveats to previous years apply:

  • These are reasonably strong options in causes of interest, and shouldn’t be taken as outright recommendations (i.e., it isn’t necessarily the case that the person making the suggestion thinks they’re the best option available across all causes).
  • The recommendations below fall within the cause areas Open Philanthropy has chosen to focus on. While this list does not expressly include GiveWell’s top charities, we believe those organizations to be the most cost-effective, evidence-backed giving opportunities available to donors today, and expect that some readers of this post might want to give to them.
  • Many of these recommendations appear here because they are particularly good fits for individual donors - due to being able to make use of fairly arbitrary amounts of donations from individuals, and in some cases because the recommender thought they’d be particularly likely to appeal to readers. This shouldn’t be seen as a list of our strongest grantees overall (although of course there may be overlap).
  • Our explanations for why these are strong giving opportunities are very brief and informal, and we don’t expect individuals to be persuaded by them unless they put a lot of weight on the judgment of the person making the suggestion.

In addition, we’d add that these recommendations are made by the individual program officers or teams cited, and do not necessarily represent my (Holden’s) personal or Open Phil’s institutional “all things considered” view.

Note that we are no longer including “Why we haven’t fully funded it” information for each option. In most cases, these grants are coming from limited per-focus-area budgets.

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Open Philanthropy is interested in when AI systems will be able to perform various tasks that humans can perform (“AI timelines”). To inform our thinking, I investigated what evidence the human brain provides about the computational power sufficient to match its capabilities. I consulted with more than 30 experts, and considered four methods of generating estimates, focusing on floating point operations per second (FLOP/s) as a metric of computational power.

The full report on what I learned is here. This blog post is a medium-depth summary of some context, the approach I took, the methods I examined, and the conclusions I reached. The report’s executive summary is a shorter overview.

In brief, I think it more likely than not that 1015 FLOP/s is enough to perform tasks as well as the human brain (given the right software, which may be very hard to create). And I think it unlikely (<10%) that more than 1021 FLOP/s is required.1 But I’m not a neuroscientist, and the science here is very far from settled.2 I offer a few more specific probabilities, keyed to one specific type of brain model, in the report’s appendix.

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In arriving at our funding priorities—including criminal justice reform, farm animal welfare, pandemic preparedness, health-related science, and artificial intelligence safety—Open Philanthropy has pondered profound questions. How much should we care about people who will live far in the future? Or about chickens today? What events could extinguish civilization? Could artificial intelligence (AI) surpass human intelligence?

One strand of analysis that has caught our attention is about the pattern of growth of human society over many millennia, as measured by number of people or value of economic production. Perhaps the mathematical shape of the past tells us about the shape of the future. I dug into that subject. A draft of my technical paper is here. (Comments welcome.) In this post, I’ll explain in less technical language what I learned.

It’s extraordinary that the larger the human economy has become—the more people and the more goods and services they produce—the faster it has grown on average. Now, especially if you’re reading quickly, you might think you know what I mean. And you might be wrong, because I’m not referring to exponential growth. That happens when, for example, the number of people carrying a virus doubles every week. Then the growth rate (100% increase per week) holds fixed. The human economy has grown super-exponentially. The bigger it has gotten, the faster it has doubled, on average. The global economy churned out $74 trillion in goods and services in 2019, twice as much as in 2000.1 Such a quick doubling was unthinkable in the Middle Ages and ancient times. Perhaps our earliest doublings took millennia.

If global economic growth keeps accelerating, the future will differ from the present to a mind-boggling degree. The question is whether there might be some plausibility in such a prospect. That is what motivated my exploration of the mathematical patterns in the human past and how they could carry forward. Having now labored long on the task, I doubt I’ve gained much perspicacity. I did come to appreciate that any system whose rate of growth rises with its size is inherently unstable. The human future might be one of explosion, perhaps an economic upwelling that eclipses the industrial revolution as thoroughly as it eclipsed the agricultural revolution. Or the future could be one of implosion, in which environmental thresholds are crossed or the creative process that drives growth runs amok, as in an AI dystopia. More likely, these impulses will mix.

I now understand more fully a view that shapes the work of Open Philanthropy. The range of possible futures is wide. So it is our task as citizens and funders, at this moment of potential leverage, to lower the odds of bad paths and raise the odds of good ones.

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This post compares our progress with the goals we set forth a year ago, and lays out our plans for the coming year.

In brief:

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Since our last hiring update, we have had a lot of new staff join Open Philanthropy. I’d like to use this post to introduce the new members of our team. We’re excited to have them!

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As part of our work on biosecurity and pandemic preparedness, we have contracted Good Judgment Inc. to expand its efforts to aggregate, publish, and track forecasts about the COVID-19 pandemic, with the hope that these forecasts can help improve planning by health security professionals and the broader public, limit the spread of the virus, and save lives.

The initial set of predictions, available here, are aggregated from forecasts by professional “Superforecasters,” who qualified by being in the most accurate 1-2% of forecasters from a large-scale, government-funded series of forecasting tournaments that ran from 2011-2015 (see Superforecasting) and, since then, by being in the top handful of forecasters from Good Judgment’s public forecasting platform, Good Judgment Open.

We may commission additional forecasts related to COVID-19 in the coming months, and we welcome suggestions of well-formed questions for which regularly updated forecasts would be especially helpful to public health professionals and the broader public. If you would like to suggest one or more questions for potential forecasting, please fill out this short form, especially if you are a medical or public health professional, and especially if you know how to state the forecasting question(s) precisely enough that it’s clear how to decide later how the question(s) resolved.

We’ve been funding scientific research and policy analysis on biosecurity and pandemic preparedness for several years and are glad to support the work many of our grantees are already doing to respond to this crisis. We’re continuing to support them and are pursuing other opportunities to help mitigate the effects of this pandemic, which we expect to share more about in the future.

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Last year, the year before, the year before that, and the year before that, we published a set of suggestions for individual donors looking for organizations to support. This year, we are repeating the practice and publishing updated suggestions from Open Philanthropy program staff who chose to provide them.

The same caveats as in previous years apply:

  • These are reasonably strong options in causes of interest, and shouldn’t be taken as outright recommendations (i.e., it isn’t necessarily the case that the person making the suggestion thinks they’re the best option available across all causes).
  • In many cases, we find a funding gap we’d like to fill, and then we recommend filling the entire funding gap with a single grant. That doesn’t leave much scope for making a suggestion for individuals. The cases listed below, then, are the cases where, for one reason or another, we haven’t decided to recommend filling an organization’s full funding gap, and we believe it could make use of fairly arbitrary amounts of donations from individuals.
  • Our explanations for why these are strong giving opportunities are very brief and informal, and we don’t expect individuals to be persuaded by them unless they put a lot of weight on the judgment of the person making the suggestion.

In addition, we’d add that these recommendations are made by the individual program officers or teams cited, and do not necessarily represent my (Holden’s) personal or Open Phil’s institutional “all things considered” view. Also, I just want to note that per our policy we’re no longer publishing all potentially relevant relationships.

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