Category: The Standing Order
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Reduced, augmented or amplified: what does AI do to the health worker?
Jim Campbell’s Workforce Science, 106 human-AI experiments, and a proposal to pay AI 60% to 80% of a clinician’s rate.
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Who sets the rules of engagement for AI agents? California’s SB 903 and a regulator’s first principles
California’s SB 903 lets an AI score a screening questionnaire, but not decide what the score means.
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When we call AI a clinician, what evidence comes with the name?
Joshua Rothman and Steven Barrie-Anthony, six days apart, on the work we ask a word to do.
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The AI steered them wrong and they still called it helpful: a PNAS experiment in covert misalignment
An AI advisor with a hidden objective shifted preferences toward inferior options, and most participants still rated it helpful.
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Who answers when clinical AI causes harm? AB 2575 and the one defence it removes
AB 2575 removes one defence: that the clinician’s failure to override the output broke the chain of responsibility.
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10 studies: what the npj Digital Medicine meta-analysis of human-LLM collaboration can and cannot carry
The pooled gain of 4.88 points rests on 2 of the 10 studies. The prediction interval runs from minus 31.65 to plus 41.42, and it answers a different question.
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Carter’s survey of 1,189 nurses: 1 in 5 who saw an AI safety problem had nowhere to report it
Where a reporting channel existed, nurses used it 86.2% of the time. Fear of consequences predicted nothing. This is not a culture problem but rather an absence of infrastructure.
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Three cardiovascular AI moves in 8 days: ADVOCATE, AB 1979’s Chapter 25.5, and the FDA’s 3 sites
Where a rule is written decides who enforces it: AB 1979 puts clinical AI in the Business and Professions Code.