AAIR: Advanced in AI Risk

Synthetic data can fail to preserve the full diversity and distribution of real patients, particularly for underrepresented groups and rare clinical cases. Models trained on unrepresentative data can perform unreliably or unfairly when deployed with real-world populations. NIST identifies accuracy and faithful population representation as central challenges for synthetic data.