AI Agents Need Consent: IBM Explains Agentic Consent

Autonomy in AI Agents: AI agents’ ability to act autonomously necessitates the introduction of robust consent mechanisms beyond traditional models to ensure safety and responsibility.
Agentic Consent Explained: AI agents execute actions rather than generating output, requiring a new approach to consent that specifies action parameters, scope, and lifetime of delegation.
Types of Consent: Miller distinguishes between expressed consent, explicitly given by users, and implied consent, which can be inferred from user actions or circumstances.
Traditional Consent Limitations: Static IT consent mechanisms are inadequate for the dynamic nature of AI agents which can learn and adapt autonomously, necessitating context-aware, dynamic consent management.
Key Pillars of Agentic Consent: Miller outlines three pillars—transparency, revocability, and personalization—to effectively manage agentic consent and ensure safety and trust in AI systems.
Implementation of Agentic Consent: The new approach emphasizes a granular, context-aware consent granting process, wherein agents operate under specific, explicitly given permissions.

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