How to Build Privacy-Preserving Evaluation Benchmarks with Synthetic Data
Validating AI systems requires benchmarksβdatasets and evaluation workflows that mimic real-world conditionsβto measure accuracy, reliability, and safety...
Validating AI systems requires benchmarksβdatasets and evaluation workflows that mimic real-world conditionsβto measure accuracy, reliability, and safety before deployment. Without them, youβre guessing. But in regulated domains such as healthcare, finance, and government, data scarcity and privacy constraints make building benchmarks incredibly difficult. Real-world data is locked behindβ¦