TLDR:
Key points:
- The FDA, along with regulators from Canada and the U.K., published best practices for applying AI in patient care.
- Transparency in AI development is crucial for healthcare professionals, patients, administrators, payors, and governing bodies.
The FDA, along with Health Canada and the U.K. Medicines and Healthcare products Regulatory Agency, has released a set of best practices for the development of medical devices powered by machine learning. The focus is on transparency in AI development to ensure that healthcare professionals, patients, and other stakeholders have trust in the devices being used.
Transparency includes clear communication of a product’s intended use, rates of performance, and internal logic whenever possible. This approach also emphasizes human-centered design in product development, aiming to create products that provide a positive user experience.
This collaboration underscores the global effort to address AI in healthcare and promote health equity. The integration of guiding principles for transparency throughout the product lifecycle helps ensure safe and effective utilization of machine learning-enabled medical devices.
The Biden administration has also prioritized AI safety, establishing the U.S. AI Safety Institute to evaluate AI in healthcare and develop technical guidance for regulatory rulemaking. The goal is to establish security and equity standards for AI systems, further enhancing transparency and trust in AI-enabled devices.
Overall, the focus on transparency in AI development by regulatory bodies like the FDA, Health Canada, and the U.K. Medicines and Healthcare products Regulatory Agency is essential for promoting trust and safety in the use of AI-powered medical devices.