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Runtime Governance for AI Agents: Policies on Paths

This paper proposes a formal framework for runtime governance of AI agents, defining compliance policies as deterministic functions mapping agent identity, partial path, proposed next action, and organizational state to a policy violation probability. The authors argue that runtime evaluation is the general case for path-dependent policies and provide concrete examples inspired by the AI Act, along with a reference implementation.

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Runtime Governance for AI Agents: Policies on Paths
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Under the source content permission, this page provides an editorial summary, key points, and a link to the original article.

Key points and analysis

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Key points

  • AI agents produce non-deterministic, path-dependent behavior that cannot be fully governed at design time.
  • The execution path is the central object for effective runtime governance.
  • A formal framework is presented, including deterministic compliance policy functions.
  • Runtime evaluation is the general case for handling path-dependent policies.

Highlights and analysis are generated automatically and may contain errors. Check the original source.