Academic Journal
Governing AI for Mental Health: Fragmented State Approaches and the Case for a Federal Framework.
| Τίτλος: | Governing AI for Mental Health: Fragmented State Approaches and the Case for a Federal Framework. |
|---|---|
| Συγγραφείς: | Aldhalimi A; Yale University School of Medicine, New Haven, CT, United States.; The Mental Health AI Policy Project, Washington, DC, United States. |
| Πηγή: | JMIR mental health [JMIR Ment Health] 2026 Jul 28; Vol. 13, pp. e96389. Date of Electronic Publication: 2026 Jul 28. |
| Τύπος έκδοσης: | Journal Article |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: JMIR Publications Inc Country of Publication: Canada NLM ID: 101658926 Publication Model: Electronic Cited Medium: Internet ISSN: 2368-7959 (Electronic) Linking ISSN: 23687959 NLM ISO Abbreviation: JMIR Ment Health Subsets: MEDLINE |
| Imprint Name(s): | Original Publication: Toronto : JMIR Publications Inc., [2014]- |
| Ιατρικοί όροι (MeSH): | Artificial Intelligence*/legislation & jurisprudence , Mental Health Services*/legislation & jurisprudence , Mental Health*/legislation & jurisprudence , State Government* , Government Regulation*, Humans ; United States |
| Περίληψη: | State-level regulation of AI used for mental health is emerging in the absence of a federal framework. States are taking different approaches to regulation, resulting in a fragmented regulatory landscape. This Viewpoint aims to identify the governance approaches that US states are using to regulate the use of AI in mental health and analyze the limitations of each. A 4-state case analysis was conducted using the statutory text of bills and laws in Illinois, Utah, New York, and Nevada. Two governance approaches were identified. The first regulates the use of AI in clinical contexts, and the second regulates the technology itself. Some states have combined elements of both approaches to address AI use more comprehensively. While these approaches aim to mitigate harm, they differ in where they believe risk lies in the use of AI for mental health support. The limitations of these divergent approaches include uneven protections for consumers and regulatory uncertainty for developers, vendors, deployers, and clinicians. Because AI in mental health operates across both clinical and consumer domains, neither approach alone can address the risks associated with its use for mental health support. A coordinated, risk-based federal regulatory floor is needed to ensure consistent protections across states. (©Abir Aldhalimi. Originally published in JMIR Mental Health (https://mental.jmir.org), 28.07.2026.) |
| Contributed Indexing: | Keywords: AI; AI governance; AI regulation; artificial intelligence; chatbot; generative AI; health care policy; law; legislation; mental health; mental health policy; policy |
| Entry Date(s): | Date Created: 20260728 Date Completed: 20260729 Latest Revision: 20260729 |
| Update Code: | 20260730 |
| DOI: | 10.2196/96389 |
| PMID: | 42517516 |
| Βάση Δεδομένων: | MEDLINE |
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