AI Governance at the Frontier
CSET report presents an analytic approach for U.S. policymakers to deconstruct assumptions behind five frontier AI governance proposals and preserve decision-making flexibility under uncertainty.
Research
CSET
Research on AI governance and emerging technology. cset.georgetown.edu
Focus All
Topic Regulation & law
Source CSET · 11
Date Any time
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AI Incidents: Key Components for a Mandatory Reporting Regime
Proposes standardized key components for a mandatory AI incident reporting regime, covering incident type, harm severity, technical data, affected parties and context, drawing on transportation, healthcare and cybersecurity reporting.
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Governing AI with Existing Authorities
Argues U.S. agencies should first use existing sectoral authorities to govern AI safety, using commercial aviation as a case study to identify gaps needing new legislation.
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Enabling Principles for AI Governance
CSET report arguing that effective AI governance requires tracking AI risks and incidents, building regulator AI literacy, and keeping policies adaptable as AI evolves.
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Putting Teeth into AI Risk Management
A CSET report arguing that federal procurement rules, as used in cybersecurity, can enforce AI risk management and development best practices among government suppliers, and offering recommendations for doing so.
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An Argument for Hybrid AI Incident Reporting
Proposes a federated hybrid framework of mandatory, voluntary and citizen reporting to standardize and aggregate AI incident data, drawing lessons from other sectors' incident databases.
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Comment on OMB RFC on Advancing Governance, Innovation, and Risk Management for Agency Use of Artificial Intelligence Draft Memorandum
CSET's comment to OMB on draft federal guidance covering Chief AI Officers, AI risk management and agency AI adoption, arguing for monitoring foreign government AI use and calibrating security practices to offensive uses.
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Repurposing the Wheel: Lessons for AI Standards
A CSET and CNAS workshop report drawing lessons from finance, worker safety, cybersecurity and medical-device standards to inform AI standards development and governance.
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AI Incident Collection: An Observational Study of the Great AI Experiment
CSET explainer defining criteria for AI incident collection and comparing mandatory, voluntary and citizen reporting models for tracking real-world AI harms.
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One Size Does Not Fit All
CSET's research agenda argues AI assessment must cover diverse products and tools, and proposes studying testing, standards, auditing and certification to reduce AI safety and trust risks.
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Classifying AI Systems
CSET brief developing and testing frameworks to classify AI systems along policy-relevant dimensions, comparing over 1,800 classifications to support risk assessment, governance and system management.