AI Has a Darker Side in Healthcare, Expert Says

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LOS ANGELES — Artificial intelligence (AI) has its benefits in the healthcare sphere, but there are also pitfalls to watch out for, one expert said here at the Association of Health Care Journalists Fall Summit.

“Digital technology has been used for decades to increase extraction of labor from workers and degrade working conditions,” said Mishal Khan, PhD, senior researcher at the Technology and Work Program of the UC Berkeley Labor Center in California. “Even if they don’t lose a single job to AI, it doesn’t mean there are no harms to workers.”

Khan divided AI’s uses in the workplace into three categories:

Electronic monitoring. This involves use of cameras to monitor workers — classic examples include Uber drivers and delivery truck drivers for signs of fatigue and other issues, or construction zones to make sure workers are using safety equipment.

Algorithmic management. AI software may be used to listen in on phone conversations between workers and customers and coach workers on what to say — for example, “Show more empathy” or “Be more sympathetic,” Khan said.

Task or job automation: This refers to when specific parts of a job are outsourced to AI.

In general, said Kahn, use of AI risks the development or exacerbation of potential harms such as:

• Job loss
• Theft of work product
• Job de-skilling
• Lower wages and wage theft
• Work speed-up and injuries
• Discrimination
• Suppression of labor organizing
• Loss of autonomy and control

In her study of AI’s potential healthcare effects, Khan found that de-skilling — in which humans lose specialized skills due to AI or other automation taking over those tasks — was a particular concern, and could threaten healthcare workers’ scope of practice.

That observation was echoed by Tina Hernandez-Boussard, PhD, professor of biomedical informatics at Stanford University in California, who spoke at another conference session. She mentioned that a group of medical residents was recently sent to Uganda to help out at a particular hospital’s cardiac ward. However, they lost electricity and there was no AI to read EKGs. “The residents were not able to synthesize information in a way they were confident” to give recommendations, Hernandez-Boussard noted.

Alienation and detachment from patients is another worry, Khan said, especially with automated patient handoffs. “Workers are concerned about what this is doing to patient relationships,” she pointed out, adding that there is also the issue of liability: If a mistake is made as the result of an AI recommendation, who will be held accountable?

The spread of ambient scribes is a further concern, she continued. “Workers are asking what data are being collected by these systems about them. [Scribes] are ostensibly for patient safety, but will data be collected to make decisions about [the workers]?”

The “gigification” of healthcare jobs may also be coming, warned Khan. For example, nursing platforms that are algorithmically managed might have nurses bidding for their shifts, and algorithms could predict the lowest wage a nurse will accept.

State legislatures are taking action on some of these issues, Khan said. For instance, bills passed in Illinois and Vermont prohibit the replacement of mental health workers with AI, and a California law bars companies from advertising an AI chatbot as a health professional. A bill being considered in California would prevent workers from having to train their replacements, including an AI replacement.

“AI can definitely have benefits for workers, but in the absence of real power, we’re seeing more harms than benefits,” Khan noted. “Tech is not good or bad, but neither is it neutral.”

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