Going forwards, LTFF is likely to be a bit more stringent (~15-20%?[1] Not committing to the exact number) about approving mechanistic interpretability grants than in grants in other subareas of empirical AI Safety, particularly from junior applicants. Some assorted reasons (note that not all fund managers necessarily agree with each of them):
Relatively speaking, a high fraction of resources and support for mechanistic interpretability comes from other sources in the community other than LTFF; we view support for mech interp as less neglected within the community.
Outside of the existing community, mechanistic interpretability has become an increasingly “hot” field in mainstream academic ML; we think good work is fairly likely to come from non-AIS motivated people in the near future. Thus overall neglectedness is lower.
While we are excited about recent progress in mech interp (including some from LTFF grantees!), some of us are suspicious that even success stories in interpretability are that large a fraction of the success story for AGI Safety.
Some of us are worried about field-distorting effects of mech interp being oversold to junior researchers and other newcomers as necessary or sufficient for safe AGI.
A high percentage of our technical AIS applications are about mechanistic interpretability, and we want to encourage a diversity of attempts and research to tackle alignment and safety problems.
We wanted to encourage people interested in working on technical AI safety to apply to us with proposals for projects in areas of empirical AI safety other than interpretability. To be clear, we are still excited about receiving mechanistic interpretability applications in the future, including from junior applicants. Even with a higher bar for approval, we are still excited about funding great grants.
We tentatively plan on publishing a more detailed explanation about the reasoning later, as well as suggestions or a Request for Proposals for other promising research directions. However, these things often take longer than we expect/intend (and may not end up happening), so I wanted to give potential applicants a heads-up.
Operationalized as “assuming similar levels of funding in 2024 as in 2023, I expect that about 80-85% of the mech interp projects we funded in 2023 will be above the 2024 bar.”
Going forwards, LTFF is likely to be a bit more stringent (~15-20%?[1] Not committing to the exact number) about approving mechanistic interpretability grants than in grants in other subareas of empirical AI Safety, particularly from junior applicants. Some assorted reasons (note that not all fund managers necessarily agree with each of them):
Relatively speaking, a high fraction of resources and support for mechanistic interpretability comes from other sources in the community other than LTFF; we view support for mech interp as less neglected within the community.
Outside of the existing community, mechanistic interpretability has become an increasingly “hot” field in mainstream academic ML; we think good work is fairly likely to come from non-AIS motivated people in the near future. Thus overall neglectedness is lower.
While we are excited about recent progress in mech interp (including some from LTFF grantees!), some of us are suspicious that even success stories in interpretability are that large a fraction of the success story for AGI Safety.
Some of us are worried about field-distorting effects of mech interp being oversold to junior researchers and other newcomers as necessary or sufficient for safe AGI.
A high percentage of our technical AIS applications are about mechanistic interpretability, and we want to encourage a diversity of attempts and research to tackle alignment and safety problems.
We wanted to encourage people interested in working on technical AI safety to apply to us with proposals for projects in areas of empirical AI safety other than interpretability. To be clear, we are still excited about receiving mechanistic interpretability applications in the future, including from junior applicants. Even with a higher bar for approval, we are still excited about funding great grants.
We tentatively plan on publishing a more detailed explanation about the reasoning later, as well as suggestions or a Request for Proposals for other promising research directions. However, these things often take longer than we expect/intend (and may not end up happening), so I wanted to give potential applicants a heads-up.
Operationalized as “assuming similar levels of funding in 2024 as in 2023, I expect that about 80-85% of the mech interp projects we funded in 2023 will be above the 2024 bar.”