Announcing the AIPolicyIdeas.com Database

Link post

Executive Summary

  • AIPolicyIdeas.com is a new database that compiles AI policy ideas from various sources. It’s intended to help AI policy practitioners and researchers quickly review high-impact, high-feasibility AI policy ideas, inform decisions on what to push for or research, and identify gaps in knowledge for future work. (Alternate link for if any issues arise with the AIPolicyIdeas.com URL.)

  • This was created relatively quickly. Users are encouraged to conduct their own research and analysis before making any decisions.

  • Submit ideas through this form.

  • If you’re working on existential-risk-relevant AI policy or related research, request access to the database via this form.

    • Other people can also use GCR Policy’s related public database.

    • Approval for accessing the AI policy ideas database is not guaranteed. We appreciate your understanding if your application is not approved.

We are excited to announce the launch of AIPolicyIdeas.com, a database compiling AI policy ideas from various sources across the longtermist AI governance community and beyond. The database prioritizes inclusion of policy ideas that may help reduce catastrophic risk from AI and may be implementable in the US in the near- or medium-term (in the next ~5-10 years). The database includes policy ideas of varying levels of expected impact, clarity about how impactful they’d be, and feasibility.

The ideas were curated by Abi Olvera from various sources such as Google Docs, the GCR Policy database, individual submissions, and public reports. For most ideas, we have included information on its source, relevant topic area, relevant U.S. agency, as well as loose ratings estimating expected levels of impact, feasibility, and specificity, and degree of confidence/​certainty.

Collection Process: Abi started off with a collection of lists of AI policy ideas from personal Google Docs, contacts, conversations, and public reports. To avoid redundancy, ideas were only added if they contained unique ideas not already on the database. The two largest sources of AI ideas were RP’s Survey on intermediate goals in AI governance and ideas shared by the GCR Policy team. Additional ideas will be gradually added from similar sources and a form for idea submission.

Loose Ratings: To help sort the ideas, we used a loose five-point scale for impact, confidence in our impact assessment, feasibility, and specificity. These ratings were assigned by the original author, the GCR Policy evaluation team, or Abi. However, the ratings were not rigorously assessed and come from various sources, including different assessors with their biases.

Note that most choices about what to include in the database and what ratings to give were made by Abi alone, without someone else reviewing that.

Negative Impacts Not Well Accounted For: We want to make it clear that while we have included a range of policy ideas in this database, some may have lower confidence and unclear levels of expected impact. Therefore, potential negative impacts are not well represented in this database. We encourage users to exercise caution when considering ideas, particularly those with uncertain impacts, and to conduct their research and analysis before making any decisions.

Flag if You’re Researching or Available for Expertise on an Idea: We hope this database will serve as a useful resource for effective policymaking and research that can help make a positive impact on society. Researchers and policy practitioners can engage with the database by reviewing ideas, filtering them by relevant agency, and adding their names to the “Person Researching or Familiar With” column to collaborate with others. Users can also help keep the database up-to-date by sharing relevant ideas through the provided form.

Please reach out to me if you’d like to add a large collection to this database or have recommendations/​suggestions for improvement.

Acknowledgements

This is a blog post from Rethink Priorities–a think tank dedicated to informing decisions made by high-impact organizations and funders across various cause areas. The author is Abi Olvera. Thanks to Amanda El-Dakhakhni for their guidance on this project and to Michael Aird, Ashwin Acharya, John Croxton, Markus Anderljung, Rumtin Sepasspour, Marie Buhl, Alex Lintz, Max Rauker, Renan Araujo, Emma Bluemke, Rose Hadshar, and many others for their helpful feedback.


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