Synthetic data’s compliance pitch: EU regulator guidance, NIH global health use case, and a legal “responsible AI” argument

EDPS published a regulator-oriented overview positioning synthetic data as a privacy-preserving enabler for ML training, transfer learning, and testing under EU governance constraints. NIH highlighted synthetic data for safer medical data sharing in low-resource settings, including GAN approaches such as CTGAN. A legal commentary argued synthetic data can reduce privacy, IP, and bias-related risks as part of responsible AI strategy.