Synthetic Data
Training or test data generated by a model rather than collected from the real world.
Synthetic data fills gaps where real data is scarce, sensitive, or expensive — rare edge cases, privacy-restricted records, balanced examples of a minority class. The risk is compounding: a model trained on its own kind of output can drift away from reality and amplify existing bias rather than correcting it.
In practice: Generating 5,000 plausible support tickets to cover a scenario you have three real examples of.