The illusion of safety: A report to the FDA on AI healthcare product approvals

Abstract

Artificial intelligence is rapidly transforming healthcare, offering promising advancements in diagnosis, treatment, and patient outcomes. However, concerns regarding the regulatory oversight of artificial intelligence driven medical technologies have emerged, particularly with the U.S. Food and Drug Administration's current approval processes. This paper critically examines the U.S. Food and Drug Administration's regulatory framework for artificial intelligence powered healthcare products, highlighting gaps in safety evaluations, post-market surveillance, and ethical considerations. Artificial intelligence's continuous learning capabilities introduce unique risks, as algorithms evolve beyond their initial validation, potentially leading to performance degradation and biased outcomes. Although the U.S. Food and Drug Administration has taken steps to address these challenges, such as artificial intelligence/machine learning-based software as a medical device action plan and proposed regulatory adjustments, significant weaknesses remain, particularly in real-time monitoring, transparency and bias mitigation. This paper argues for a more adaptive, community-engaged regulatory approach that mandates extensive post-market evaluations, requires artificial intelligence developers to disclose training data sources, and establishes enforceable standards for fairness, equity, and accountability. A patient-centered regulatory framework must also integrate diverse perspectives to ensure artificial intelligence technologies serve all populations equitably. By fostering an agile, transparent, and ethics-driven oversight system, the U.S. Food and Drug Administration can balance innovation with patient safety, ensuring that artificial intelligence-driven medical technologies enhance, rather than compromise, healthcare outcomes.

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