Long Term Future Fund: November grant decisions
Hey everyone. The Long Term Future Fund published it’s latest grant decisions a few days ago, and cross posting it here seemed like a good idea. Happy to answer any questions you have.
November 2018 - Long-Term Future Fund Grants
Fund: Long-Term Future Fund
Payout date: November 29, 2018
Payout amount: $95,500.00
Grant author(s): Alex Zhu, Helen Toner, Matt Fallshaw, Matt Wage, Oliver Habryka
The Long-Term Future Fund has decided on a grant round of approximately USD 95,500, to a mix of newer and more established projects (details below).
In order to close a grant round before the start of Giving Season, we ran a very short application process, and made decisions on a shorter timeline than we plan to in the future. This short timeline meant that there were many applications that we saw as promising, but did not have time to evaluate sufficiently to decide to fund them, so we did not end up granting all of the available funds in this round (approximately USD 120,000). In future grant rounds, we anticipate having more time, and therefore being more likely to spend down the entirety of the fund. We may explicitly reach out to some applicants to suggest they re-submit their applications for future rounds.
Funding to new or smaller projects
AI summer school (Jan Kulveit): USD 21,000
This grant is to fund the second year of a summer school on AI safety, aiming to familiarize potential researchers with interesting technical problems in the field. Last year’s iteration of this event appears to have gone well, based both on public materials and on private knowledge some of us have about participants and their experiences. We believe that well-run education efforts of this kind are valuable (where “well-run” refers to the quality of the intellectual content, the participants, and the logistics of the event), and feel confident enough that this particular effort will be well-run that we decided to support it. This grant fully funds Jan’s request.
Online forecasting community (Ozzie Gooen): USD 20,000
Ozzie sought funding to build an online community of EA forecasters, researchers, and data scientists to predict variables of interest to the EA community. Ozzie proposed using the platform to answer a range of questions, including examples like “How many Google searches will there be for reinforcement learning in 2020?” or “How many plan changes will 80,000 hours cause in 2020?”, and using the results to help EA organizations and individuals to prioritize. We decided to make this grant based on Ozzie’s experience designing and building Guesstimate, our belief that a successful project along these lines could be very valuable, and some team members’ discussions with Ozzie about this project in more detail. This grant funds the project’s basic setup and initial testing.
AI Safety Unconference (Orpheus Lummis and Vaughn DiMarco): CAD 6,000 (approx USD 4,500)
Orpheus Lummis and Vaughn DiMarco are organizing an unconference on AI Alignment on the last day of the NeurIPS conference, with the goal of facilitating networking and research on AI Alignment among a diverse audience of AI researchers with and without safety backgrounds.
We evaluated this grant on similar grounds to the AI-Summer School grant above; based on direct interactions we’ve had with some of the organizers and the calibre of some of the participating established AI Alignment organizations we feel that the project deserves funding. Our understanding is that the organizers are still in the process of finalizing whether or not to go ahead with the unconference, so this funding is conditional on them deciding to proceed. This grant would fully fund Orpheus’ request.
Funding to established organizations
Machine Intelligence Research Institute: USD 40,000
MIRI is seeking funding to pursue the research directions outlined in its recent update. We believe that this research represents one promising approach to AI alignment research. According to their fundraiser post, MIRI believes it will be able to find productive uses for additional funding, and gives examples of ways additional funding was used to support their work this year.
Ought: USD 10,000
Ought is a nonprofit aiming to implement AI alignment concepts in real-world applications. We believe that Ought’s approach is interesting and worth trying, and that they have a strong team. Our understanding is that hiring is currently more of a bottleneck for them than funding, so we are only making a small grant. Part of the aim of the grant is to show Ought as an example of the type of organization we are likely to fund in the future.
In total, we received over 50 submissions for funding from smaller projects. Of those submissions, we would have been interested in granting about USD 250 000 (not counting grants to larger or more established organizations), which is more than we expected given the very short application period. This leaves us optimistic about being able to recommend grants of similar quality in the future, for larger funding rounds.
It’s difficult to estimate how much total room for regranting we have, but our rough estimate would be that at least in the near term we can get a similar level of applications every 3 months, resulting in a total of ~USD 800 000 per year for smaller projects we would be interested in funding. Depending on the funding needs of major organizations, and assuming that we judge a 40:60 balance between smaller projects and established organizations to be the best use of resources, then we would estimate that we would be comfortable with regranting about 2 million USD over the calendar year.