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I think the general problem is the law says certain correlations are fair to use and others are not. If you can prove the AI model has no way to separate out wh
by TimPC 4y ago
I think the general problem is the law says certain correlations are fair to use and others are not. If you can prove the AI model has no way to separate out which is which you have a fairly sizeable amount of evidence the AI is discriminating. Likely enough evidence for a civil case.
Usually showing that input data is biased in some way or contains a potentially bad field will result in winning a discrimination case.
If neither side can conclusively prove what the model is doing but the plaintiff shows it was trained on data that allows for discrimination and the model is designed to learn patterns in its training data then the defendant is on the hook for showing the model is unbiased. For the most part people design input data uncritically and some of the fields allow for discrimination.
- thaumasiotes 4y ago> but the plaintiff shows it was trained on data that allows for discrimination That's all data; there would be no need to show anything. There was a paper a while ago by a team of doctors who wanted to use classifiers on X-ray images and FREAKED OUT when they realized that the first thing the classifier did was categorize every image by the race of the patient. As they note, it will always do this regardless of whether the race of the patient is present in the input data. (Because obviously, the race of the patient is part of the information conveyed by the structure of their body, which is what an X-ray shows.)