How MATS addresses “mass movement building” concerns

By Ryan Kidd @ 2023-05-04T00:55 (+79)

Recently, many AI safety movement-building programs have been criticized for attempting to grow the field too rapidly and thus:

  1. Producing more aspiring alignment researchers than there are jobs or training pipelines;
  2. Driving the wheel of AI hype and progress by encouraging talent that ends up furthering capabilities;
  3. Unnecessarily diluting the field’s epistemics by introducing too many naive or overly deferent viewpoints.

At MATS, we think that these are real and important concerns and support mitigating efforts. Here’s how we address them currently.

Claim 1: There are not enough jobs/funding for all alumni to get hired/otherwise contribute to alignment

How we address this:

Claim 2: Our program gets more people working in AI/ML who would not otherwise be doing so, and this is bad as it furthers capabilities research and AI hype

How we address this:

MATS Summer 2023 interest form: “How did you hear about us?” (381 responses)

Claim 3: Scholars might defer to their mentors and fail to critically analyze important assumptions, decreasing the average epistemic integrity of the field

How we address this:


We appreciate feedback on all of the above! MATS is committed to growing the alignment field in a safe and impactful way, and would generally love feedback on our methods. More posts are incoming!


Akash @ 2023-05-04T01:32 (+18)

Glad to see this write-up & excited for more posts.

I think these are three areas that MATS has handled well. I'd be especially excited to hear more about areas where MATS thinks it's struggling, MATS is uncertain, or where MATS feels like it has a lot of room to grow. Potential candidates include:

Other things I'm be curious about:

Ryan Kidd @ 2023-05-04T18:27 (+3)
  • We broadened our advertising approach for the Summer 2023 Cohort, including a Twitter post and a shout-out on Rob Miles' YouTube and TikTok channels. We expected some lowering of average applicant quality as a result but have yet to see a massive influx of applicants from these sources. We additionally focused more on targeted advertising to AI safety student groups, given their recent growth. We will publish updated applicant statistics after our applications close.
  • In addition to applicant selection and curriculum elements, our Scholar Support staff, introduced in the Winter 2022-23 Cohort, supplement the mentorship experience by providing 1-1 research strategy and unblocking support for scholars. This program feature aims to:
    • Supplement and augment mentorship with 1-1 debugging, planning, and unblocking;
    • Allow air-gapping of evaluation and support, improving scholar outcomes by resolving issues they would not take to their mentor;
    • Solve scholars’ problems, giving more time for research.
  • Defining "good alignment research" is very complicated and merits a post of its own (or two, if you also include the theories of change that MATS endorses). We are currently developing scholar research ability through curriculum elements focused on breadth, depth, and epistemology (the "T-model of research"):
  • Our Alumni Spotlight includes an incomplete list of projects we highlight. Many more past scholar projects seem promising to us but have yet to meet our criteria for inclusion here. Watch this space.
  • Since Summer 2022, MATS has explicitly been trying to parallelize the field of AI safety as much as is prudent, given the available mentorship and scholarly talent. In longer-timeline worlds, more careful serial research seems prudent, as growing the field rapidly is a risk for the reasons outlined in the above article. We believe that MATS' goals have grown more important from the perspective of timelines shortening (though MATS management has not updated on timelines much as they were already fairly short in our estimation).
  • MATS would love to support senior research talent interested in transitioning into AI safety! Our scholars generally comprise 10% Postdocs, and we would like this number to rise. Currently, our advertising strategy is contingent on the AI safety community adequately targeting these populations (which seems false) and might change for future cohorts.
Joseph Lemien @ 2023-05-04T15:11 (+6)

Just to make this a little more accessible to people who aren't familiar with SERI-MATS, MATS is Machine Learning Alignment Theory Scholars Program, a training program for young researchers who want to contribute to AI alignment research.

Ryan Kidd @ 2023-05-04T18:32 (+1)

Thanks Joseph! Adding to this, our ideal applicant has:

  • an understanding of the AI alignment research landscape equivalent to having completed the AGI Safety Fundamentals course;
  • previous experience with technical research (e.g. ML, CS, maths, physics, neuroscience, etc.), ideally at a postgraduate level;
  • strong motivation to pursue a career in AI alignment research, particularly to reduce global catastrophic risk.

MATS alumni have gone on to publish safety research (LW posts here), join alignment research teams (including at Anthropic and MIRI), and found alignment research organizations (including a MIRI team, Leap Labs, and Apollo Research). Our alumni spotlight is here.