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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 holds hospitals and clinicians back from adopting 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.
Shares A public registry of every AI model used in cancer care, How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals, AI that is built but not validated or deployed.
Shares A public registry of every AI model used in cancer care, How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals, AI that is built but not validated or deployed.
Shares A public registry of every AI model used in cancer care, How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals, AI that is built but not validated or deployed.
Shares How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals, AI that is built but not validated or deployed.
Shares How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals, AI that is built but not validated or deployed.
Shares How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals, AI that is built but not validated or deployed.
Shares How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals, AI that is built but not validated or deployed.
Shares How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals, AI that is built but not validated or deployed.
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