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Inaccessible training data risk for AI

Inaccessible training data risk for AI

Risks associated with output
Explainability
Amplified

Description

Without access to the training data, the types of explanations a model can provide are limited and more likely to be incorrect.

Why is inaccessible training data a concern for foundation models?

Low quality explanations without source data make it difficult for users, model validators, and auditors to understand and trust the model.

Parent topic: AI risk atlas

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