Synthetic Data

Artificially generated data that mimics the statistical properties of real-world datasets without containing actual personal or sensitive records. Synthetic data is produced using generative models, statistical sampling, or rule-based simulation. It is used to train and test AI systems in privacy-sensitive domains — such as healthcare, finance, and HR — where using real personal data would create legal or ethical risk. While synthetic data reduces privacy exposure, it can introduce or amplify biases from the original data it was generated from, requiring careful validation before use.

A health startup uses synthetic patient records to train a diagnostic AI model, avoiding the need to access real patient data during development — while still validating the model against a small real-world test set before deployment.