Junior researchers are often wondering what they should work on. To potentially help, we asked people at the Centre for the Governance of AI for research ideas related to longtermist AI governance. The compiled ideas are developed to varying degrees, including not just questions, but also some concrete research approaches, arguments, and thoughts on why the questions matter. They differ in scope: while some could be explored over a few months, others could be a productive use of a PhD or several years of research.
We do not make strong claims about these questions, e.g. that they are the absolute top priority at current margins. Each idea only represents the views of the person who wrote it. The ideas aren’t necessarily original. Where we think someone is already working on or has done thinking about the topic before, we’ve tried to point to them in the text and reach out to them before publishing this post.
If you are interested in pursuing any of these projects, please let us know by filling out this form. We may be able to help you find mentorship, advice, or collaborators. You can also fill out the form if you’re intending to work on the project independently, so that we can help avoid duplication of effort. If you have feedback on the ideas, feel free to email researchideas@governance.ai.
You can find the ideas here. Our colleagues at the FHI AI Safety team put together a corresponding post with AI safety research project suggestions here.
Other Sources
Other sources of AI governance research projects include:
Some AI Governance Research Ideas
Junior researchers are often wondering what they should work on. To potentially help, we asked people at the Centre for the Governance of AI for research ideas related to longtermist AI governance. The compiled ideas are developed to varying degrees, including not just questions, but also some concrete research approaches, arguments, and thoughts on why the questions matter. They differ in scope: while some could be explored over a few months, others could be a productive use of a PhD or several years of research.
We do not make strong claims about these questions, e.g. that they are the absolute top priority at current margins. Each idea only represents the views of the person who wrote it. The ideas aren’t necessarily original. Where we think someone is already working on or has done thinking about the topic before, we’ve tried to point to them in the text and reach out to them before publishing this post.
If you are interested in pursuing any of these projects, please let us know by filling out this form. We may be able to help you find mentorship, advice, or collaborators. You can also fill out the form if you’re intending to work on the project independently, so that we can help avoid duplication of effort. If you have feedback on the ideas, feel free to email researchideas@governance.ai.
You can find the ideas here. Our colleagues at the FHI AI Safety team put together a corresponding post with AI safety research project suggestions here.
Other Sources
Other sources of AI governance research projects include:
AI Governance: A Research Agenda, Allan Dafoe
Research questions that could have a big social impact, organised by discipline, 80,000 Hours
The section on AI in Legal Priorities Research: A Research Agenda, Legal Priorities Project
Some parts of A research agenda for the Global Priorities Institute, Global Priorities Institute
AI Impact’s list of Promising Research Projects
Phil Trammell and Anton Korinek’s Economic Growth under Transformative AI
Luke Muehlhauser’s 2014 How to study superintelligence strategy
You can also look for mentions of possible extensions in papers you find compelling
A list of the ideas in the document:
The Impact of US Nuclear Strategists in the early Cold War
Transformative AI and the Challenge of Inequality
Human-Machine Failing
Will there be a California Effect for AI?
Nuclear Safety in China
History of existential risk concerns around nanotechnology
Broader impact statements: Learning lessons from their introduction and evolution
Structuring access to AI capabilities: lessons from synthetic biology
Bubbles, Winters, and AI
Lessons from Self-Governance Mechanisms in AI
How does government intervention and corporate self-governance relate?
Summary and analysis of “common memes” about AI, in different communities
A Review of Strategic-Trade Theory
Mind reading technology
Compute Governance ideas
Compute Funds
Compute Providers as a Node of AI Governance
China’s access to cutting edge chips
Compute Provider Actor Analysis