ASSESSING AI FOR CLINICAL CARE AND RESEARCH

While advances in AI technology abound, there is a growing concern that a lack of standards and safety protocols for the use of AI in both care and research is now the chief barrier to progress. While no single technology company, regulator, organization, or hospital holds the solution, the need for some consensus and ground rules has become self-evident. This talk will review efforts towards this goal with a focus on selected efforts, such as that in the UK by the MHRA, in the US by NAMI, and broadly across the published literature/public internet.

Learning Objective 1: Assess the state of AI regulation both in the United States as well as abroad.

Learning Objective 2: Identify common themes around safety and rigor across various AI regulation or guidance systems

References

Dwyer B, Flathers M, Sano A, Dempsey A, Cipriani A, Gazi AH, Hill B, Gorban C, Rodriguez CI, Stromeyer IV C, King D. Mindbench. ai: an actionable platform to evaluate the profile and performance of large language models in a mental healthcare context. NPP—Digital Psychiatry and Neuroscience. 2025 Nov 14;3(1):28. Torous J, Cipriani A. A Paradigm Shift in Progress: Generative AI’s Evolving Role in Mental Health Care. JMIR Mental Health. 2025 Dec 17;12:e82369.