Last updated: Dec 12, 2024
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
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.