Record summary
A quick snapshot of what this page covers.
Techniques0Attack methods connected to this risk.
Mitigations0Defenses that may help with related attacks.
Domain7. AI System Safety, Failures, & LimitationsThe broad risk area this belongs to.
Risk profile
How this risk is described and categorized.
"When an LLM is configured to evaluate the performance of another model or AI system, it may produce incorrect evaluation outputs [122, 147]. For example, it may give a higher rating to a more verbose answer or an answer from a particular political stance. If an LLM-based evaluation is integrated into the training of a new model, the trained model could develop in a way that specifically finds and exploits limitations in the evaluator’s metrics."
Domain7. AI System Safety, Failures, & Limitations
Subdomain7.1 > AI pursuing its own goals in conflict with human goals or values
Entity2 - AI
Intent2 - Unintentional
Timing1 - Pre-deployment
CategoryModel Evaluations
SubcategoryGeneral Evaluations (Incorrect outputs of GPAI evaluating other AI models)
Suggested mitigations
Defenses that may help with related attacks.
No propagated mitigations. No defense is available through the connected attack methods.
Source
Research source for this risk, when available.
Included resource
Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems
Original source
MIT AI Risk Repository
Open the public repository used for AI risk records and taxonomy fields.