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Unrepresentative risk testing risk for AI
Last updated: Dec 12, 2024
Unrepresentative risk testing risk for AI
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Non-technical risks
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Description

Testing is unrepresentative when the test inputs are mismatched with the inputs that are expected during deployment.

Why is unrepresentative risk testing a concern for foundation models?

If the model is evaluated in a use, context, or setting that is not the same as the one expected for deployment, the evaluations might not accurately reflect the risks of the model.

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