Data Leakage

In the context of AI, data leakage refers to the introduction of information into the training data that the system is expected to infer but should not legitimately have access to during model training. This results in a model that appears to perform well during evaluation on the test set but demonstrates poor performance during deployment when evaluated on new data sets.