AI
Synthetic data
Training data generated by a model rather than collected from real-world sources, used to augment datasets or avoid privacy constraints.
Synthetic data can fill gaps where real data is scarce, sensitive or expensive to label. The risk is model collapse: training on synthetic outputs from the same model family amplifies biases and reduces diversity. Provenance tracking and mixing synthetic with real data are the usual mitigations.