arXiv Artificial Intelligence

Mapping U.S. Federal AI Governance Against Sector Vulnerability

1 hour ago 16.09.2026 07:00 👁 1 views
Mapping U.S. Federal AI Governance Against Sector Vulnerability

Quick summary

arXiv:2609.16260v1 Announce Type: cross Abstract: Artificial intelligence (AI) poses different levels of risk across sectors, but are these differences reflected in U.S. federal AI governance? To help answer this question, we assess 684 federal AI governance documents for their coverage of 14 sectors and 24 AI risks. We measure coverage as breadth (i.e., how frequently the risk or sector is addressed across documents) and depth (i.e., how substantively the risk or sector is discussed). We then compare sector coverage patterns for each of the 24 risks with vulnerability assessments from a Delph

Key takeaways

  • arXiv:2609.16260v1 Announce Type: cross Abstract: Artificial intelligence (AI) poses different levels of risk across sectors, but are these differences reflected in U.S.
  • To help answer this question, we assess 684 federal AI governance documents for their coverage of 14 sectors and 24 AI risks.
  • We measure coverage as breadth (i.e., how frequently the risk or sector is addressed across documents) and depth (i.e., how substantively the risk or sector is discussed).

Why it matters

This development is a reminder to test misuse and data-leak scenarios alongside speed and quality. Trust should come from testable controls and clear failure reporting, not protection claims alone.

Kaynak sitede devamını oku: arXiv Artificial Intelligence ↗