Executive summary: This personal post outlines ten AI safety project ideas the author believes are promising and tractable for reducing catastrophic risks from transformative AI, ranging from field-building and communications to technical governance and societal resilience, while emphasizing that these suggestions are subjective, non-exhaustive, and not official Open Philanthropy recommendations.
Key points:
Talent development in AI security — There’s a pressing need for more skilled professionals in AI security, especially outside of labs; a dedicated field-building program could help fill this gap.
New institutions for technical governance and safety monitoring — The author proposes founding research orgs focused on technical AI governance, independent lab monitors, and “living literature reviews” to synthesize fast-moving discourse.
Grounding AI risk concerns in real-world evidence — Projects like tracking misaligned AI behaviors “in the wild” and building economic impact trackers could provide valuable empirical grounding to complement theoretical arguments.
Strategic communication and field support infrastructure — The author advocates for a specialized AI safety communications consultancy and a detailed AI resilience funding blueprint to help turn broad concern into effective action.
Tools and startups for governance and transparency — The post suggests developing AI fact-checking tools and AI-powered compliance auditors, though the latter comes with significant security caveats.
Caveats and epistemic humility — The author stresses these are personal, partial takes (not official Open Phil policy), that many of the ideas have some precedent, and that readers should build their own informed visions rather than copy-paste.
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Executive summary: This personal post outlines ten AI safety project ideas the author believes are promising and tractable for reducing catastrophic risks from transformative AI, ranging from field-building and communications to technical governance and societal resilience, while emphasizing that these suggestions are subjective, non-exhaustive, and not official Open Philanthropy recommendations.
Key points:
Talent development in AI security — There’s a pressing need for more skilled professionals in AI security, especially outside of labs; a dedicated field-building program could help fill this gap.
New institutions for technical governance and safety monitoring — The author proposes founding research orgs focused on technical AI governance, independent lab monitors, and “living literature reviews” to synthesize fast-moving discourse.
Grounding AI risk concerns in real-world evidence — Projects like tracking misaligned AI behaviors “in the wild” and building economic impact trackers could provide valuable empirical grounding to complement theoretical arguments.
Strategic communication and field support infrastructure — The author advocates for a specialized AI safety communications consultancy and a detailed AI resilience funding blueprint to help turn broad concern into effective action.
Tools and startups for governance and transparency — The post suggests developing AI fact-checking tools and AI-powered compliance auditors, though the latter comes with significant security caveats.
Caveats and epistemic humility — The author stresses these are personal, partial takes (not official Open Phil policy), that many of the ideas have some precedent, and that readers should build their own informed visions rather than copy-paste.
This comment was auto-generated by the EA Forum Team. Feel free to point out issues with this summary by replying to the comment, and contact us if you have feedback.