*This post was co-authored by Josh Yoo, legal intern at Robinson+Cole. Josh is not admitted to practice law.

Health care entities maintain compliance programs in order to comply with the myriad, changing laws and regulations that apply to the health care industry. Although laws and regulations specific to the use of artificial intelligence (AI) are limited at this time and in the early stages of development, current law and pending legislation offer a forecast of standards that may become applicable to AI. Health care entities may want to begin to monitor the evolving guidance applicable to AI and start to integrate AI standards into their compliance programs in order to manage and minimize this emerging area of legal risk.

Executive Branch: Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence

Following Executive Order 13960 and the Blueprint for an AI Bill of Rights, Executive Order No. 14110 (EO) amplifies the current key principles and directives that will guide federal agency oversight of AI. While still largely aspirational, these principles have already begun to reshape regulatory obligations for health care entities. For example, the Department of Health and Human Services (HHS) has established an AI Task Force to regulate AI in accordance with the EO’s principles by 2025. Health care entities would be well-served to monitor federal priorities and begin to formally integrate AI standards into their corporate compliance plans.

• Confidentiality and Security: Federal scrutiny of the privacy and security of entrusted information extends to AI’s interactions with data as a core obligation. This general principle also manifests in more specific directives throughout the EO. The EO also orders the HHS AI Task Force to incorporate “measures to address AI-enhanced cybersecurity threats in the health and human services sector.”

• Transparency: The principle of transparency refers to an AI user’s ability to understand the technology’s uses, processes, and risks. Health care entities will likely be expected to understand how their AI tools collect, process, and predict data. The EO envisions labelling requirements that will flag AI-generated content for consumers as well.

• Governance: Governance applies to an organization’s control over deployed AI tools. Internal mechanical controls, such as evaluations, policies, and institutions, may ensure continuous control throughout the AI’s life cycle. The EO also emphasizes the importance of human oversight. Responsibility for AI implementation, review, and maintenance can be clearly identified and assigned to appropriate employees and specialists.

• Non-Discrimination: AI must also abide by standards that protect against unlawful discrimination. For example, the HHS AI Task force will be responsible for ensuring that health care entities continuously monitor and mitigate algorithmic processes that could contribute to discriminatory outcomes. It will be important to permit internal and external stakeholders to have access to equitable participation in the development and use of AI.

National Institute of Standards and Technology: Risk Management Framework

The National Institute of Standards and Technology (NIST) published a Risk Management Framework for AI (RMF) in 2023. Similar to the EO, the RMF outlines broad goals (i.e., Govern, Map, Measure, and Manage) to help organizations address and manage the risks of AI tools and systems. A supplementary NIST “Playbook”  provides actionable recommendations that implement EO principles to assist organizations to proactively mitigate legal risk under future laws and regulations. For example, a health care organization may uphold AI governance and non-discrimination by deploying a diverse, AI-trained compliance team.Continue Reading Forecasting the Integration of AI into Health Care Compliance Programs