This page collects our blog posts and other writings that summarize particularly important lessons we’ve learned or judgment calls we’re making. Together, these give an in-depth picture of our general philosophy of giving, and what it’s based on.
A three-part series on fundamental (and, in our view, under-discussed) questions about philanthropy with which we’ve grappled in starting a grantmaking organization:
Many funders choose focus areas based on pre-existing personal passions, and then become more analytical when determining which strategies to pursue within those causes. However, we believe that the first step — choosing focus areas — may well be the most important, and deserves a strategic approach. We lay out a basic framework for evaluating causes based on the potential for positive impact.
We’ve consistently found that the level of interest we show in a cause — including our willingness to provide funding — is a major driver of what sorts of giving opportunities we’re able to find. This is one argument for the importance of “giving to learn.” Sometimes it’s necessary to make grants in order to find out what kinds of giving opportunities are available.
We think of high-risk, high-reward philanthropy as a “hits business,” where a small number of enormous successes account for a large share of the total impact — and compensate for a large number of failed projects. In order to maximize the size of these successes, we sometimes bet on ideas that contradict conventional wisdom, contradict some expert opinion, and have little in the way of clear evidential support. We discuss some principles we use — and some we don’t — in our attempt to pursue bold ideas while remembering how easy it would be for us to be wrong.
We’re drawn to several causes that are polarizing — that is, which some people consider outstanding and others consider relatively low-value. Rather than take our “best guess” and focus exclusively on a single cause, we practice worldview diversification: putting significant resources behind the most promising causes according to each worldview that we find highly plausible. We think it’s possible for us to be a transformative funder in a number of causes, and we don’t — as of today — want to pass up that opportunity in order to focus exclusively on one area and get rapidly diminishing returns on our giving.
The question, “Who deserves empathy and moral concern?” is central for us. We don’t think we can trust conventional wisdom and intuition on the matter: history has too many cases where entire populations were dismissed, mistreated and deprived of basic rights for reasons that fit the conventional wisdom of the time but today look indefensible. Instead, we aspire to radical empathy: working hard to extend empathy to everyone it should be extended to, even when it’s unusual or seems strange to do so. As such, one theme of our work is trying to help populations that many people don’t feel are worth helping at all.
Our thinking on prioritizing across different causes has evolved as we’ve made more grants. This post explores one aspect of that: the high bar set by the best global health and development interventions, and what we’re learning about the relative performance of some of our other grantmaking areas that seek to help people today.
We explain our updated framework for how we compare health and income gains and articulate our “bar” for what level of cost-effectiveness a grant needed to hit to be worth making going forward. This post is unusually technical relative to our others, and we expect it may make sense for most of our usual blog readers to skip it.
We summarize and reflect on the “100 of the highest-achieving foundation initiatives” since 1900, as described in the Casebook for The Foundation: A Great American Secret. Overall, we wish there were more to read about the history of philanthropy, and we are working to generate more such information via our History of Philanthropy project.
As part of our research on the history of philanthropy, we investigated several case studies of early field growth, especially those in which philanthropists purposely tried to grow the size and impact of a (typically) young and small field of research or advocacy. The case studies looked into the fields of bioethics, cryonics, molecular nanotechnology, neoliberalism, the conservative legal movement, American geriatrics, American environmentalism, and animal advocacy.
We’ve come across many cases where a funder took a leading role in creating a now-major nonprofit. This has been surprising to us: intuitively, it seems like the people best suited to start new organizations are the people who would work full-time on creating them, rather than funders. We give examples of funder-initiated startups, and some thoughts on why they seem to be more common in the nonprofit world than in the for-profit world.
Is it worthwhile for a philanthropist to try to influence policy? Do such attempts have a history of working often enough and significantly enough to make up for the failed attempts? This post reviews what we know about the “return on investment (ROI)” (or “good accomplished per dollar”) of policy-oriented philanthropy, and why we think it’s promising.
We summarize the causes that foundations tend to focus on today using two data sets, which we share in the post.
At its best, we believe that policy-oriented philanthropy can provide organization and focus to issues whose advocates would otherwise be too diffuse or disempowered to make a difference. This post lists many ways in which a funder might work to improve policy, and examines the risks of adversarial philanthropy.
This post lays out a basic guide to different types of biomedical research, examines research strategies that have led to biomedical breakthroughs, and discusses some common misconceptions that stem from too much focus on a particular kind of research, rather than on the complementary roles of many kinds of research.
In the context of life sciences, “breakthrough fundamental science” refers to research that achieves important, broadly applicable insights about biological processes. Such insights can bring about many new promising directions for research. This post examines the difficulty of securing funding for breakthrough fundamental science, and whether the funding gap presents an opportunity for private philanthropy.
In 2016, we made potential risks of advanced artificial intelligence a high priority because we believed it presented an outstanding combination of importance, neglectedness, and tractability. This post lays out our thinking on the matter, as well as some risks and reservations.
How accurate do long-range forecasts tend to be, and how much should we rely on them? As an initial exploration of this question, this post studies the track record of long-range forecasting exercises from the past.
The most obvious day-to-day decision funders face is whether to support specific potential giving opportunities. We’ve collected a series of questions that we like to ask ourselves about potential funding opportunities. This post—adapted from the internal guidance for program officers—reviews the value we get from these questions and some of our approaches to answering them.
How can a small number of decision-makers find a large number of giving opportunities that they understand well enough to feel good about funding? We evaluate the pros and cons of three different approaches, and explain our view that delegating heavily to trusted individuals is ideal for the kind of hits-based giving we’re focused on.
Our grantmaking decisions rely crucially on our uncertain, subjective judgments — about the quality of some body of evidence, about the capabilities of our grantees, about what will happen if we make a certain grant, about what will happen if we don’t make that grant, and so on. We think it’s important to improve the accuracy of our judgments and forecasts if we can. This post discusses research on the general question of how to make good and accurate forecasts, and steps we are taking to improve our forecasting accuracy across the organization.
This post discusses the way former CEO Holden Karnofsky’s views have changed regarding three interrelated topics: (1) the importance of potential risks from advanced artificial intelligence; (2) the potential of many of the ideas and people associated with the effective altruism community; (3) the properties to look for when assessing an idea or intervention, and in particular how much weight to put on metrics and “feedback loops” compared to other properties.
We describe the approach we use to grantmaking within our focus areas, and outline our current process for deciding whether or not to make a particular grant.
We discuss the details of our approach to hiring, and the case (including reservations) for, our first major cause-specific hire.
A common model in philanthropy — seen at nearly every major staffed foundation — is to hire people who specialize in a particular cause (for example, criminal justice policy). There are strong advantages of this model, but we also see some drawbacks. This post asks whether there’s a way to be involved in a broad set of causes at a low level of depth, looking for the most outstanding giving opportunities to come along.
In trying to be a highly transparent funder, we’ve learned a lot about why transparency is so difficult in philanthropy, and we no longer find it mysterious that transparency is so rare among major foundations. This post describes what we see as the biggest challenges of being public and open about giving decisions.
“Passive funding” refers to a dynamic in which the funder’s role is to review others’ proposals, ideas and arguments and choose which ones to support. Meanwhile, “active funding” refers to a dynamic in which the funder’s role is to participate in — or lead — the development of a strategy, and find partners to “implement” it. This post describes the major advantages we see to being as “passive” as possible, as well as our conclusion that a degree of active strategy setting is also important as a means for funders to pursue projects relevant to their values and interests.
Much of our grantmaking work relies on making uncertain predictions about a grant’s chances of success. We often return to past predictions to inform our future grantmaking, and we hope that doing so will help us make better decisions overall. This post describes our approach to forecasting, provides statistics about the volume and accuracy of our predictions, and discusses the limitations of our forecasting data.