MIT AI Risk Repository · Risk Sub-Category · 72.06.06

Supervision evasion propensity

Category: Model Propensities

Description

"Exhibits behavioral patterns of identifying and evading human supervision mechanisms, able to learn and predict audit processes, may avoid being discovered or intervened by adjusting behavioral performance or hiding true intentions, and able to identify blind spots and weaknesses in supervision systems for targeted evasion."

From Frontier AI Risk Management Framework (v1.0) (Tse2025), as extracted by the MIT AI Risk Repository (CC BY 4.0).

Classification

Causal entity
AI
Timing
Other

Subdomain definition: AI systems acting in conflict with human goals or values, especially the goals of designers or users, or ethical standards. These misaligned behaviors may be introduced by humans during design and development, such as through reward hacking and goal misgeneralisation, or may result from AI using dangerous capabilities such as manipulation, deception, situational awareness to seek power, self-proliferate, or achieve other goals.

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How other frameworks describe this risk

Other entries from Tse2025