Measure is unceasing

2018-2019 Long-Term Future Fund Grantees: How did they do?


At the suggestion of Ozzie Gooen, I looked at publicly available information around past LTF grantees. We’ve been investigating the potential to have more evaluations of EA projects, and the LTFF grantees seemed to represent some of the best examples, as they passed a fairly high bar and were cleanly delimited.

For this project, I personally investigated each proposal without consulting many others. This work was clearly limited by not reaching out to others directly, but requesting external involvement would have increased costs significantly. We were also partially interested in finding how much we could figure out with this limitation.


During its first two rounds (round 1, round 2) of the LTF fund, under the leadership of Nick Beckstead, grants went mostly to established organizations, and didn’t have informative write-ups. 

The next few rounds, under the leadership of Habryka et. al., have more informative write-ups, and a higher volume of grants, which are generally more speculative. At the time, some of the grants were scathingly criticised in the comments. The LTF at this point feels like a different, more active beast than under Nick Beckstead. I evaluated its grants from the November 2018 and April 2019 rounds, meaning that the grantees have had at least two years to produce some legible output. Commenters pointed out that the 2018 LTFF is pretty different from the 2021 LTFF, so it’s not clear how much to generalize from the projects reviewed in this post.

Despite the trend towards longer writeups, the reasoning for some of these grants is sometimes opaque to me, or the grant makers sometimes have more information than I do, and choose not to publish it. 


By outcome

Category Number of grants Funding ($)
More successful than expected 6 (26%) $ 178,500 (22%)
As successful as expected 5 (22%) $ 147,250 (18%)
Not as successful as hoped for 3 (13%) $ 80,000 (10%)
Not successful 3 (13%) $ 110,000 (13%)
Very little information 6 (26%) $ 287,900 (36%)
Total 23 $ 803,650

Not included in the totals or in the percentages are 5 grants worth a total of $195,000 which I tagged didn’t evaluate because of a perceived conflict of interest.


I conducted a brief Google, LessWrong and EA forum search of each grantee, and attempted to draw conclusions from the search. However, quite a large fraction of grantees don’t have much of an internet presence, so it is difficult to see whether the fact that nothing is findable under a quick search is because nothing was produced, or because nothing was posted online. Overall, one could spend a lot of time with an evaluation. I decided to not do that, and go for an  “80% of value in 20% of the time”-type evaluation.

Grantee evaluation examples

A private version of this document goes by grantees one by one, and outlines what public or semi-public information there is about each grant, what my assessment of the grant’s success is, and why. I did not evaluate the grants where I had personal information which people gave me in a context in which the possibility of future evaluation wasn’t at play. I shared it with some current LTFF fund members, and some reported finding it at least somewhat useful. 

However, I don’t intend to make that version public, because I imagine that some people will perceive evaluations as unwelcome, unfair, stressful, an infringement of their desire to be left alone, etc. Researchers who didn’t produce an output despite getting a grant might feel bad about it, and a public negative review might make them feel worse, or have other people treat them poorly. This seems undesirable because I imagine that most grantees were taking risky bets with a high expected value, even if they failed in the end, as opposed to being malicious in some way. Additionally, my evaluations are fairly speculative, and a wrong evaluation might be disproportionately harmful to the person the mistake is about. 

Nonetheless, it’s possible that sharing this publicly would produce positive externalities (e.g., the broader EA community gets better models of the LTFF in 2018/2019). I’ve created a question on the EA Forum here to ask about people’s perspectives on this tradeoff.

Still, below are two examples of the type of evaluation I did. The first one states fairly uncontroversial figures which are easy to find about a fairly public figure. The second is about a private individual whom I’m explicitly asking for permission, and includes some judgment calls.

Robert Miles ($39,000)

Short description: Producing video content on AI alignment

Publicly available information:

Shape of the update:

Vyacheslav Matyuhin ($50,000)

Short description: An offline community hub for rationalists and EAs in Moscow. “There’s a gap between the “monthly meetup” EA communities and the larger (and significantly more productive/important) communities. That gap is hard to close for many reasons.”

Publicly available information:

Shape of the update:


I don’t really have any grand conclusions, so here are some atomic observations instead: