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PacingResearch

Foundations

Selected reading

Three starting points for studying the pace of AI. All are external work, credited to their authors.

Pacing the Frontier: A Framework & Research Agenda ↗

Raymond Douglas, Charles Dillon, Nikola Moore, Gavin Leech, Shahar Avin, and collaborators

A broad account of interventions affecting AI development, deployment, and diffusion. Organizes open questions around incentives, intervention design, and the full lifecycle of a restriction.

Read as a research agenda: its proposed interventions and open questions are not established effects.

Computing Power and the Governance of Artificial Intelligence ↗

Girish Sastry et al. · 2024 · arXiv:2402.08797

Examines compute as an instrument of AI governance: why it may be tractable to govern, which policy uses it could support, and the limitations and risks of doing so.

Read alongside the operational question: which property would a proposed measure actually observe or constrain?

Model evaluation for extreme risks ↗

Toby Shevlane et al. · 2023 · arXiv:2305.15324

Sets out a framework for evaluating dangerous capabilities and alignment, with implications for training, deployment, transparency, and security.

Evaluation informs a decision. Its conclusions remain bounded by the system, elicitation method, and conditions tested.