Google has published a whitepaper outlining its framework for evaluating artificial intelligence in health, developed with health experts Dr. Elizabeth McGlynn and Dr. Dana Gelb Safran. The framework assesses AI models across accuracy, safety and usefulness, using a mix of closed-question benchmarks, autoraters and expert review. This approach is designed to address both common and high-risk scenarios in healthcare, where AI adoption is accelerating.
The company says it uses this framework to determine whether its models deliver accurate and safe responses in health settings. By releasing its methodology, Google aims to promote transparency and support others in the health sector, including developers, researchers and clinicians, to build trustworthy AI tools.
For regulated organisations in healthcare and pharma, the framework may influence expectations from regulators and partners around transparency and safety in AI deployment. It may also shape due diligence requirements when adopting or procuring AI-driven solutions.
Executives should watch for how regulators and industry groups respond, and whether similar frameworks become a reference point for compliance or procurement standards.
