The case for donor lotteries is based on assumptions that don’t hold up to scrutiny. Based on how donor lotteries have performed in practice there is little reason to think that (as GWWC put it a few months ago when launching the 2024 lottery) “we believe donor lotteries are one of the most effective ways for smaller donors to give, provided you're comfortable with the approach.” In the past, even stronger claims have been made about the benefits of donor lotteries.
Questionable assumptions include:
- Donor Lotteries assume anyone can be a good grant evaluator. Even among a donor base of EAs, there’s no reason to think that everyone participating in a lottery is equally capable of being a good evaluator. If one assumes non-EA participants, this assumption becomes even less realistic. Different people have different strengths, but the lottery model assigns evaluation responsibility based on randomness rather than relevant skill.
- Donor Lotteries assume winners’ work will be leveraged. In practice, lottery winners rarely publish their work (the last published writeup is from the 2018-2019 lottery). It’s also rare for lottery winners to become professional grantmakers, so it’s questionable whether any additional evaluation knowledge they acquire is leveraged beyond the lottery.
- Donor lotteries assume there’s demand for the model. Donor lotteries have typically been in the ballpark of a few hundred thousand dollar, and often significantly smaller. One likely explanation is that the model is highly counterintuitive, and difficult to explain to casual donors (or anyone who isn’t already familiar with it).
- Donor lotteries assume the model improves impact/dollar significantly, and does so for a significant number of dollars. Lotteries are unlikely to improve impact/dollar significantly, as the model is mostly used by (or even understandable by) people who are already EAs. Casual donors whose impact could be considerably increased are unlikely to understand or participate in a lottery. And historically lotteries have only been modest size, so they are not impacting a large number of dollars.
Donor Lotteries were an interesting experiment because they address an important observation: there are economies of scale when giving. However, I’d argue EA Funds is a much better implementation model. EA Funds is easily understandable (to EAs and non-EAs alike), uses evaluators that are chosen for their ability in that area (rather than by random selection), has a better track record of publishing grant writeups than donor lotteries, and adds evaluation capacity more efficiently over time (since fund managers are relatively static as opposed to donor lotteries where a new evaluator is selected and needs to start training from scratch with each new lottery). EA Funds already does a much higher donation volume than donor lotteries, and it would be preferable to continue building these economies of scale than to divide resources across multiple projects with similar goals.
>If it's about reducing the influence of large donors, what is the incentive for large donors to participate?
Even large donors suffer from the problem of the time cost in evaluating charities. Imagine there are 100 large donors. Imagine a"democratic lottery", now turned oligarchic lottery, chooses the committee and voter weights based on the amount donated.
The incentive for wealthy individuals to participate is to reduce the huge evaluation costs. The oligarchic lottery can be trusted to on average, statistically represent their personal moral weights, proportionate to the wealth they donate. The small lottocratic committee makes the big decisions, so the large whole doesn't have to make any decisions.
What incentive is there for wealthy people to donate to a democratic instead of oligarchic lottery? Even some wealthy people might believe in equal consideration of other people's opinions, that their personal wealth does not make them better at utilitarian or moral calculation. If so, wealthy individuals can still reap the benefits of the lottery and reduce their personal evaluation costs.