In Spring 2023, the Berkeley AI Safety Initiative for Students (BASIS) organized an alignment research program for students, drawing inspiration from similar programs by Stanford AI Alignment^[1] and OxAI Safety Hub. We brought together 12 researchers from organizations like CHAI, FAR AI, Redwood Research, and Anthropic, and 38 research participants from UC Berkeley and beyond.

Here is the link to SPAR’s website, which includes all of the details about the program. We’ll be running the program again in the Fall 2023 semester as an intercollegiate program, coordinating with a number of local groups and researchers from across the globe.

If you are interested in supervising an AI safety project in Fall 2023, learn more here and fill out our project proposal form, ideally by August 25. Applications for participants will be released in the coming weeks.

Motivation

Since a primary goal of university alignment organizations is to produce counterfactual alignment researchers, there seems to be great value in encouraging university students to conduct research in AI safety, both for object-level contributions and as an opportunity to gain experience and test fit. While programs like AI Safety Fundamentals, representing the top of a “funnel” of engagement in the alignment community, have been widely adopted as a template for the introductory outreach of university groups, we do not think there are similarly ubiquitous options for engaged, technically impressive students interested in alignment to further their involvement productively. Research is not the only feasible way to do this, but it holds various advantages: many of the strongest students are more interested in research than other types of programs that might introduce them to AI safety, projects have the potential to produce object-level results, and research project results provide signal among participants of potential for future alignment research.

Many alignment university groups have run research programs on a smaller scale and have generally reported bottlenecks such as lack of organizer capacity and difficulty attaining mentorship and oversight on projects; we believe an intercollegiate and centralized-administration model can alleviate these problems.

Additionally, we believe that many talented potential mentors with “implementation-ready” project ideas would benefit from a streamlined opportunity to ...

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