OnCo
ideasIdea

A liability framework for clinical AI: safe harbour for clinicians, liability for makers

Make clear who is responsible when an AI tool contributes to a mistake: protect doctors who use approved tools as intended, and hold makers responsible for the tool's performance.

Liability uncertainty is a major reason hospitals and clinicians do not adopt AI: the clinician may bear responsibility for a tool they cannot inspect. The proposal is legislation or regulatory guidance establishing a safe harbour for clinicians who follow a registered, validated model within its labelled use, coupled with product-liability accountability for developers for performance within the labelled use, and a no-fault compensation scheme for patients harmed by AI errors, as exists for vaccines in several countries.

Hypothesis
A clear liability framework will increase adoption of validated AI tools by clinicians and reduce defensive overriding, without an increase in patient harm, in jurisdictions that adopt it versus those that do not.
Rationale
Liability shields (Good Samaritan laws, vaccine injury compensation) have changed professional behaviour where uncertainty deterred beneficial action; surveys of clinicians rank liability among the top barriers to AI use.
What would test it
Compare AI adoption and override rates in a jurisdiction that adopts the framework with matched jurisdictions over three years; track claims and compensation cases.
Maturity
speculative
Who has to act
policy
Cost to try
Small (under $1M)
Years to first evidence
3
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bottlenecks

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AI that is built but not validated or deployed