AI Regulation and Legal Trends in Healthcare: A U.S. and International Overview
Artificial intelligence (AI) and machine learning (ML) are rapidly transforming healthcare, bringing new capabilities and challenges. From diagnostic tools to generative AI applications for coding and data analysis, these technologies are integral to innovation and improved patient care. However, this rapid evolution has triggered significant regulatory and legal shifts in the United States, Europe, and China, alongside existing concerns about privacy, cybersecurity, and intellectual property (IP).
U.S. AI Regulations: Federal and State Developments
In the U.S., the federal government is navigating the complexities of AI regulation. A Biden-era executive order emphasizing consumer protection was followed by Executive Order 14179, which aims to minimize the impact of federal rulemaking on AI innovation. The National Institute of Standards and Technology (NIST) has developed an AI framework. Despite proposed federal legislation, there has been little momentum, with many legislators hesitant to impede technological advancements.
In the absence of federal action, states like California, Colorado, and Utah have enacted their own AI regulations. The Colorado AI Act is particularly relevant to healthcare, targeting high-risk AI systems. It requires developers to provide detailed documentation and impact assessments. Although there are exemptions for certain FDA-regulated products and HIPAA-regulated entities in non-high-risk scenarios, the law’s breadth and the interpretation of these exemptions remain uncertain. A task force has been appointed to recommend changes, reflecting concerns about overbroad language and ambiguity. The approach in Colorado may serve as a model for other states and echoes principles found in European legislation.
AI Regulation in the European Union
The European Union (EU) employs the EU AI Act and the General Data Protection Regulation (GDPR) as key regulatory frameworks for AI. The EU AI Act imposes stringent requirements on high-risk AI systems, particularly those used in medical devices. These requirements include risk management, data governance, technical documentation, and transparency throughout the AI system’s lifecycle. Conformance assessments are also needed for high-risk systems, similar to those required for medical devices. Medical device manufacturers must comply with these rules by August 2, 2026, which will create added obligations on top of existing medical device regulations.
China’s Approach to AI Regulation
China is also actively addressing AI regulation, aiming to balance AI safety, security, innovation, and leadership. Current regulations primarily focus on generative AI, but broader AI development is likely to face further regulation in the future. Similar to recent U.S. policy, China is seeking to balance safeguards and innovation.
Intellectual Property Considerations
Intellectual property (IP) disputes are another active area in AI law. Numerous cases in the U.S. involve the use of copyrighted works to train AI/ML models. IP considerations apply to both sides: the unregulated use of generative AI tools may lead to IP or trade secret loss, and life sciences companies must consider how IP and data ownership rights may restrict their use of data for AI/ML model development. Court decisions will clarify these lines as case law develops.
Privacy and Cybersecurity Risks in AI Development
Privacy and cybersecurity considerations continue to impact AI/ML, both in their development and application. The use of personal data, particularly health data, for AI training remains a significant concern for both U.S. and international regulators. As companies and their vendors implement AI tools, they must carefully address privacy and cybersecurity risks. Organizations can mitigate these risks through updated policies and training, vendor risk assessments, knowledge of relevant privacy requirements, and robust contract terms.
In conclusion, the legal and regulatory environment surrounding AI and machine learning in healthcare is in a state of flux. Organizations must stay informed about developments in the U.S., EU, and China to ensure compliance, manage risks, and leverage the benefits of AI while protecting patient privacy and intellectual property.
