Pre-Deployment Information Sharing: A Zoning Taxonomy for Precursory Capabilities
Matteo Pistillo, Charlotte Stix

TL;DR
This paper introduces a zoning taxonomy for early warning of dangerous AI capabilities, proposing a structured information sharing framework among trusted actors to enhance safety and risk management.
Contribution
It develops a novel zoning taxonomy for precursory capabilities and offers detailed recommendations for information sharing aligned with AI safety commitments.
Findings
Proposes a spectrum-based zoning taxonomy for dangerous capabilities.
Recommends early sharing of precursory information within AI safety institutions.
Highlights international coordination for risk assessment across regions.
Abstract
High-impact and potentially dangerous capabilities can and should be broken down into early warning shots long before reaching red lines. Each of these early warning shots should correspond to a precursory capability. Each precursory capability sits on a spectrum indicating its proximity to a final high-impact capability, corresponding to a red line. To meaningfully detect and track capability progress, we propose a taxonomy of dangerous capability zones (a zoning taxonomy) tied to a staggered information exchange framework that enables relevant bodies to take action accordingly. In the Frontier AI Safety Commitments, signatories commit to sharing more detailed information with trusted actors, including an appointed body, as appropriate (Commitment VII). Building on our zoning taxonomy, this paper makes four recommendations for specifying information sharing as detailed in Commitment…
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Taxonomy
TopicsInformation Technology Governance and Strategy
