Living dossier · 17 linked objects · state as of
Healthcare AI governance
California passed four AI-related health measures in the 2025–2026 session and none is law: AB 2575 (tool inventories, clinical decision support, worker override) and AB 1979 completed passage; SB 503 (developer and deployer duties for biased outputs) and SB 903 (AI barred from providing or advertising therapy) are enrolled or enrolling. WHO/Europe published evidence that governance readiness, not deployment speed, is the binding constraint — as a convened expert report, not WHO policy. The European Commission designated a general AI service under platform law with obligations due end-November.
What the law provides
Medical-record content and retention are governed by state record requirements and electronic-record certification criteria; neither requires that machine-generated clinical text be identifiable as such. FDA’s clinical-decision-support policy addresses device status, not authorship. Attestation law assumes a human author.
The gap
No instrument requires provenance capture at generation, model-version recoverability, or a face-of-the-record distinction between physician and machine text. Every surveyed instrument ends at the clinician, because the clinician is the only actor already licensed, insured and disciplinable.
The KPSGILL position
Require machine-readable provenance for AI-generated clinical text at the point of generation, and move physician responsibility from authorship to clinically material adoption. The twelve-dimension readiness framework treats validation, provenance, bias monitoring, accountability allocation and model change control as separate questions.
The open question
Responsibility should follow control, and a clinician using a system she cannot inspect does not control it. Every instrument surveyed nonetheless lands responsibility on her. What allocation would survive a case where the model was right, the clinician overrode it, and the patient was harmed?
Litigation
No docket yet. The KPSGILL forecast is that contested board discipline over AI-assisted decisions arrives before any board publishes risk-tiered guidance.
Tracked legislation
| Bill | Subject | State |
|---|---|---|
| AB 2575 | Health care services: artificial intelligence | LEGISLATIVE PASSAGE COMPLETE |
| SB 503 | Health care artificial intelligence: bias in clinical decision-making and resource allocation | ENROLLED AND PRESENTED TO GOVERNOR |
| SB 903 | Artificial intelligence: mental health and the practice of therapy | LEGISLATIVE PASSAGE COMPLETE |
| AB 1979 | Health care services: artificial intelligence | LEGISLATIVE PASSAGE COMPLETE |
Everything KPSGILL has published on this
Derived from the topic entity in the entity registry. A page tagged to this topic appears here without this dossier being edited.
How progress would be measured
- Share of certified record systems capturing generation-time provenance
- Share of AI-drafted notes with recoverable model and version identity
- Board cases in which provenance was available to the adjudicator
Entity topic.healthcare-ai · all dossiers · event timeline · methodology