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A Lifecycle Management Approach Toward Delivering Safe, Effective AI-Enabled Health Care

Summary of blog post from FDA, by Troy Tazbaz:

AI’s continuous learning and adaptability pose risks, such as exacerbating biases, which can harm patients and underrepresented populations. Lifecycle Management (LCM), integral to reliable software since the 1960s, can address these challenges through structured frameworks. The AI Lifecycle (AILC) concept maps traditional Software Development Lifecycles to AI-specific phases, emphasizing systematic methods for data and model evaluation. This AILC model serves as a guide for assessing standards, tools, metrics, and best practices, promoting quality, interoperability, and ethical practices. The health care community is encouraged to engage with and refine these concepts to ensure AI’s safe and effective integration into health care. Feedback and involvement are welcomed to support the development of high-quality AI models.