Alaap B. Shah, Member of the Firm in the Health Care & Life Sciences practice, in the firm’s Washington, DC, office, co-authored the whitepaper, “Designing a Trusted Framework for the Application of AI in Health Care,” for the American Health Law Association’s “Convener on Artificial Intelligence and Health Law.”

Following is an excerpt:

The American Health Law Association (AHLA) hosted a virtual Convener on Artificial Intelligence (AI) and Health Law on November 2, 2020. AHLA Conveners gather thought leaders including regulators, clinicians, private practitioners, and other leading authorities to problem-solve through candid dialogue and frank discussion on emerging issues that impact health care and health law. Although AHLA does not engage in lobbying activities, topics discussed during AHLA Conveners frequently present a path forward to the discussion of thorny problems confronting the health care industry. In light of AI’s novel technical nature, its myriad potential applications, and its dependence on complex big data strategies, it is a particularly appropriate topic for the in-depth focus of an AHLA Convener.

The Convener participants and planning committee members have extensive expertise in big data and health care. They were tasked with identifying the elements of a trusted framework for implementing AI in the health care industry. Their positions in health systems, government, academia, private business, legal practice, clinical medicine, statistics and health information, and consumer technology provided a broad spectrum of multi-disciplinary expertise and perspectives needed for a robust and well‑informed discussion. The opinions and perspectives expressed by the participants, are theirs alone and do not reflect those of the organizations with whom they are affiliated or employed by.

This white paper summarizes the Convener discussion, which focused primarily on data privacy and security, regulation, liability allocation, intellectual property, and contracting challenges, and how these issues affect the development of a trusted framework for using AI in health care. It also provides one Author’s view of significant regulatory actions taken in the interim between the Convener and the paper’s publication.

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