> i'm not a doctor and op didn't link the article but that is absolutely what happens if you train ai on a poorly designed training set. ai will learn whatever correlates with the answers in the training set but would be extremely stupid to just assume what correlates in the training set matches reality. that completely depends on the predictive power of the model. for complex tasks, predicative power is generally dubious, but they are better than humans when it comes to binary classification. i don't think this in any way indicates a poorly designed data set, or any issues with training in general
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