Unreliable source attribution risk for AI
Description
Source attribution is the AI system's ability to describe from what training data it generated a portion or all its output. Since current techniques are based on approximations, these attributions might be incorrect.
Why is unreliable source attribution a concern for foundation models?
Low-quality attributions make it difficult for users, model validators, and auditors to understand and trust 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.