Executive summary: The author argues that international AI projects should adopt differential AI development by tightly restricting the most dangerous capabilities, especially AI that automates AI R&D, while actively accelerating and incentivizing “artificial wisdom” systems that help society govern rapid AI progress.
Key points:
Existing proposals for international AI projects focus on blanket control of frontier AI, which would block both dangerous and highly beneficial capabilities.
The author claims the core risk comes from AI that can automate ML research, engineering, or chip design, because this could trigger super-exponential capability growth and extreme power concentration.
They propose that only AI systems above a compute threshold and aimed at automating AI R&D or producing catastrophic technologies should be monopolized or banned outside an international project.
Enforcement could rely on oversight of a small number of large training runs, with audits, embedded supervisors, and severe penalties for violations.
The author argues governments should differentially accelerate “helpful” AI, including forecasting, policy analysis, ethical deliberation, negotiation support, and rapid education.
This approach could improve preparedness for rapid AI change, be more acceptable to industry, reduce incentives for international racing, and sometimes benefit even geopolitical rivals.
This comment was auto-generated by the EA Forum Team. Feel free to point out issues with this summary by replying to the comment, andcontact us if you have feedback.
Executive summary: The author argues that international AI projects should adopt differential AI development by tightly restricting the most dangerous capabilities, especially AI that automates AI R&D, while actively accelerating and incentivizing “artificial wisdom” systems that help society govern rapid AI progress.
Key points:
Existing proposals for international AI projects focus on blanket control of frontier AI, which would block both dangerous and highly beneficial capabilities.
The author claims the core risk comes from AI that can automate ML research, engineering, or chip design, because this could trigger super-exponential capability growth and extreme power concentration.
They propose that only AI systems above a compute threshold and aimed at automating AI R&D or producing catastrophic technologies should be monopolized or banned outside an international project.
Enforcement could rely on oversight of a small number of large training runs, with audits, embedded supervisors, and severe penalties for violations.
The author argues governments should differentially accelerate “helpful” AI, including forecasting, policy analysis, ethical deliberation, negotiation support, and rapid education.
This approach could improve preparedness for rapid AI change, be more acceptable to industry, reduce incentives for international racing, and sometimes benefit even geopolitical rivals.
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.