A new technique identifies and removes the training examples that contribute most to a machine-learning model’s failures. Copyright: news.mit.edu – “Researchers Reduce Bias in AI Models While Preserving or Improving Accuracy” Machine-learning models can fail when they try to make predictions for individuals who were underrepresented in the datasets they were trained on. For instance, a model that predicts the best treatment option for someo…