Legal Risks and Unanswered Questions of AI in Sleep Medicine

Legal Gray Areas of AI in Sleep Medicine

At the 39th annual meeting of the Associated Professional Sleep Societies, held in Seattle, Ramesh Sachdeva, MD, PhD, from Children’s Hospital of Michigan, presented key legal concerns surrounding the use of artificial intelligence (AI) in sleep medicine. His insights focused on clinician liability, informed consent, and the responsible integration of AI tools into patient care.

Sachdeva emphasized that AI is relatively new in the clinical setting, and the legal framework governing its use is still developing. He pointed out that the legal challenges span a broad spectrum, including civil liability, intellectual property rights, and vicarious liability. Sleep medicine is among several neurology specialties where AI has made significant inroads, from auto-scoring diagnostic tools to wearable devices that monitor sleep stages, oxygenation, and even potential sleep apnea.

Legal Responsibility and AI Errors

One pressing question is who is liable when AI tools make mistakes. Sachdeva explained that liability is case-specific and could involve the AI developer, the clinician, or the medical institution. The level of responsibility often depends on how the AI is used—whether it operates independently or supports clinical decision-making.

Given these risks, Sachdeva stressed the importance of clinicians carefully reviewing AI outputs rather than accepting them blindly. Physicians should apply their expertise to interpret AI recommendations, ensuring patient safety while leveraging AI’s potential benefits.

Informed Consent and AI Integration

Another legal consideration is informed consent when AI tools are part of diagnosis or patient monitoring. Patients should be made aware of AI’s role in their care and any associated risks. Transparency in how AI contributes to clinical decisions is essential to maintain trust and meet legal standards.

Key Takeaways for Legal Professionals

• AI in sleep medicine presents complex liability issues that lack clear legal precedents.
• Responsibility for AI errors may be shared among developers, clinicians, and institutions.
• Clinicians must remain vigilant, critically assessing AI recommendations before applying them.
• Informed consent processes need to explicitly include disclosures about AI’s role in patient care.

As AI tools become more common in healthcare, legal professionals should monitor emerging regulations and case law closely. Understanding the nuances of AI integration will be crucial for advising healthcare clients and managing liability risks effectively.

For professionals interested in expanding their knowledge of AI’s impact across industries, including healthcare, resources such as Complete AI Training’s courses by job role offer practical guidance.

References

• Sachdeva R, Goldstein C, Horsnell M, et al. Legal Issues and the Practice of Sleep Medicine: Artificial Intelligence, Machine Learning, & Emerging Technologies. Presented at SLEEP 2025, June 10, Seattle.
• Meglio, M. System Integration: How AI Is Weaving Itself into Neurology. HCPLive. December 5, 2024.