However, machine learning algorithms, which detect and exploit recurring patterns in large datasets by design, can just as easily use artifacts as real linguistic clues.
models trained on these datasets can achieve high test accuracy by exploiting artifacts but fail to generalize, e.g., they fail under adversarial evaluation (Jia and Liang, 2017;Ribeiro et al., 2018).