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AI Risk

Discrimination and Stereotype Reproduction

"General purpose AI models interpret and respond to inputs based on their training data, potentially causing Discrimination and Stereotype Reproduction. Since they are “black-box” models, the exact mechanism behind decisions remains opaque and attempts to mitigate harmful outputs are not fully reliable yet. These models have the capacity to influence a multitude of downstream applications, decisions, and processes...

AI Risk1. Discrimination & Toxicity1.1 > Unfair discrimination and misrepresentation2 - Post-deployment

Record summary

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Techniques0Attack methods connected to this risk.
Mitigations0Defenses that may help with related attacks.
Domain1. Discrimination & ToxicityThe broad risk area this belongs to.

Risk profile

How this risk is described and categorized.

"General purpose AI models interpret and respond to inputs based on their training data, potentially causing Discrimination and Stereotype Reproduction. Since they are “black-box” models, the exact mechanism behind decisions remains opaque and attempts to mitigate harmful outputs are not fully reliable yet. These models have the capacity to influence a multitude of downstream applications, decisions, and processes, thereby affecting many individuals simultaneously. The extent of this impact could outstrip the range of any single human or group of humans, amplifying the potential consequences of embedded biases or stereotypes."

Domain1. Discrimination & Toxicity
Subdomain1.1 > Unfair discrimination and misrepresentation
Entity2 - AI
Intent2 - Unintentional
Timing2 - Post-deployment
CategoryRisks from Unreliability
SubcategoryDiscrimination and Stereotype Reproduction

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.