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At the Association of Health Care Journalists Fall Summit in Los Angeles, UC Berkeley researcher Mishal Khan warned that AI in healthcare can affect workers even when it does not eliminate jobs. She and Stanford professor Tina Hernandez-Boussard raised concerns about de-skilling, monitoring, patient relationships and accountability, while describing some state legislative responses.
AI may reshape healthcare work in ways that affect workers even when it does not eliminate their jobs, Mishal Khan, a senior researcher at the UC Berkeley Labor Center, said at the Association of Health Care Journalists Fall Summit in Los Angeles. Khan warned about risks including loss of skills, closer workplace surveillance and reduced control over work, making the effects of healthcare AI a labor issue as well as a technology question.
Khan described three broad workplace uses of AI: electronic monitoring, such as cameras tracking workers; algorithmic management, in which software evaluates work or coaches employees; and automation of specific tasks. She said technologies in these categories can bring benefits, but may also contribute to job loss, lower wages, work intensification, discrimination and loss of autonomy. These were risks she identified, not findings that every AI system causes those outcomes.
In her study of AI’s potential effects in healthcare, Khan singled out de-skilling as a particular concern. When automated tools take over specialized tasks, workers may have fewer opportunities to practice them, potentially affecting their scope of practice. Stanford biomedical informatics professor Tina Hernandez-Boussard described medical residents sent to a hospital cardiac ward in Uganda who lost electricity and had no AI tool available to read electrocardiograms. She said the residents struggled to synthesize information confidently enough to make recommendations.
Khan also raised concerns about automated patient handoffs and ambient scribes, which record or document clinical encounters. Workers, she said, want to know what information these systems collect about them and whether it could be used in employment decisions. She also questioned who would be liable if a clinician made an error after following an AI recommendation. The report did not identify a specific incident or establish that a particular system had caused harm.
How AI Could Change Clinical Work
The concerns reach beyond whether AI replaces positions. If workers lose practice with clinical tasks, their confidence and ability to work without automated support could be affected. Hernandez-Boussard’s account of the residents in Uganda illustrates the issue, though it does not establish how common such a problem is or show that AI alone caused it.
Monitoring and algorithmic management could also change who controls the pace and organization of care. Khan warned that worker data collected for systems presented as safety tools could have other uses. For patients, the stakes include the quality of communication and handoffs; for healthcare organizations and policymakers, they include responsibility when automated recommendations influence decisions. The source report does not document specific patient injuries or quantify the scale of these risks.
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Three Ways AI Enters Workplaces
Khan framed healthcare AI within a broader history of workplace technology. She said digital systems have been used for decades in ways that can increase the extraction of labor and worsen working conditions. Her categories—monitoring, algorithmic management and task automation—describe different mechanisms, rather than one uniform effect of AI.
The report also cited several state policy measures. Khan said Illinois and Vermont passed bills prohibiting the replacement of mental health workers with AI, and that a California law bars companies from advertising an AI chatbot as a health professional. She also said a California bill was under consideration that would prevent workers from having to train their replacements, including an AI replacement. The report did not provide bill names, implementation details or the current status of that proposed measure.
“Even if they don’t lose a single job to AI, it doesn’t mean there are no harms to workers.”
— Mishal Khan, senior researcher at the UC Berkeley Labor Center
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Evidence and Accountability Still Open
The report does not quantify how often healthcare workers experience AI-related de-skilling, surveillance, wage effects or reduced autonomy. Khan’s concerns identify possible harms; they do not establish that all AI deployments produce them. The account of residents in Uganda is an example reported by Hernandez-Boussard, and the report gives no further details about the hospital, the residents’ training or what happened after power was lost.
It also remains unclear how ambient-scribe data are stored, who can access them, or whether employers use them to assess staff. The report raises the question of liability for mistakes linked to AI recommendations but does not describe a settled legal standard or a specific case. The status and scope of the California proposal mentioned by Khan are also not fully detailed.
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Policy and Workplace Choices Ahead
The next developments will depend on how healthcare employers adopt AI tools and whether lawmakers set limits on their use. Khan pointed to enacted measures in Illinois and Vermont and a California law on marketing AI chatbots, as well as a California bill she said was under consideration. The report does not specify a timetable for that proposal or identify upcoming votes.
For now, questions raised at the summit include whether workers can retain and practice clinical skills, what information workplace systems collect, how automated management affects job conditions, and who is accountable when AI informs care. Khan’s position was that AI can benefit workers, but that the outcomes depend in part on workers’ power in decisions about its use.
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Key Questions
What did the expert warn about?
Mishal Khan warned that AI can affect healthcare workers through monitoring, algorithmic management and task automation, including possible loss of skills and autonomy even without job cuts.
What is de-skilling in healthcare?
De-skilling refers to workers losing opportunities to practice specialized tasks when automated systems take over parts of their jobs. Khan said this could affect healthcare workers’ skills and scope of practice.
What happened to the residents in Uganda?
Stanford professor Tina Hernandez-Boussard said a group of medical residents in a hospital cardiac ward lost electricity and did not have AI available to read electrocardiograms. She said they struggled to synthesize information confidently enough to make recommendations.
Have states passed laws on AI and healthcare work?
Khan said Illinois and Vermont passed bills barring the replacement of mental health workers with AI, and that a California law bars companies from advertising an AI chatbot as a health professional. She also cited a California bill under consideration concerning workers training AI replacements; the report did not give its current status.
Who is liable if an AI recommendation contributes to an error?
That remains unresolved in the report. Khan raised liability as a concern but did not identify a specific case or a settled legal standard for responsibility.
Source: rss
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