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Output bias risk for AI

Output bias risk for AI

Risks associated with output
Fairness
New

Description

Generated model content might unfairly represent certain groups or individuals. For example, a large language model might unfairly stigmatize or stereotype specific persons or groups.

Why is output bias a concern for foundation models?

Bias can harm users of the AI models and magnify existing exclusive behaviors. Business entities can face reputational harms and other consequences.

Background image for risks associated with input
Example

Biased Generated Images

Lensa AI is a mobile app with generative features trained on Stable Diffusion that can generate “Magic Avatars” based on images users upload of themselves. According to the source report, some users discovered that generated avatars are sexualized and racialized.

Parent topic: AI risk atlas

Generative AI search and answer
These answers are generated by a large language model in watsonx.ai based on content from the product documentation. Learn more