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One using TIGTEC to explain the predictions of one\u2019s classifier must be aware of these biases in order to stand back and analyze the produced results. On the other hand, by generating unexpected counterfactual examples, we believe that TIGTEC can be useful in detecting bias in the classifier it seeks to explain. Finally, as any method based on deep learning, this method consumes energy, potentially emitting greenhouse gases. 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