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Output bias risk for AI

Output bias risk for AI

Risks associated with output
New to generative AI


Generated content might unfairly represent certain groups or individuals.

Why is output bias a concern for foundation models?

Bias can harm users of the AI models and magnify existing discriminatory behaviors. Business entities might face reputational harms, disruption to operations, and other consequences.

Background image for risks associated with input

Biased Generated Images

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

Parent topic: AI risk atlas

We provide examples covered by the press to help explain many of the foundation models' risks. Many of these events covered by the press are either still evolving or have been resolved, and referencing them can help the reader understand the potential risks and work towards mitigations. Highlighting these examples are for illustrative purposes only.

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