Some healthcare professionals believe artificial intelligence will buy them more time with patients. Others fear it puts jobs, and lives, at risk.
In a recent episode of The Pitt, a viral TV show about the inner-workings of a Pittsburgh hospital, overworked doctors battled a new antagonist: AI.
An attending physician tells her staff that the technology can cut their time spent on charting results by 80%, buying them more time to provide treatment. But later, doctors discover that the system has made up false details about a patient and confused ‘urology’ for ‘neurology’.
The problems raised in the show mirror real-life experience for medical staff navigating the new age of artificial intelligence. Hospitals world-wide are grappling with questions about the effectiveness of this technology; whether it will benefit the healthcare industry and its patients, or put them in harm’s way.
In a 2025 survey by the American Medical Association, it was reported that two out of three physicians used AI to assist with their daily work. Places with high rates of poverty and homelessness lean on this technology to provide access to those who might otherwise be incapable of seeking medical advice. In other words, AI is pushing the doctor out.
Individuals can ask chat bots to review their symptoms and spit out suggested treatments. And while this frees up more time for staff to see other patients, as well as removing barriers to treatment in a nation where healthcare is infamously inaccessible, it poses serious risks.
For starters, AI is never 100% accurate – at least not yet. Any information it generates should be reviewed by a human, which means it only adds another layer of work to already strained industries like healthcare. Given that there is even the slightest risk of misinformation that could lead to fatal results, AI’s medical use remains a taboo subject. But regardless, people from low income backgrounds should not be used as the guinea pigs.
On the face of it, medical AI sounds like the magic pill we’ve all been waiting for. Better diagnoses, personalised support for a larger number of patients. Faster drug discovery and research into diseases like cancer. But it’s not this simple in practice. And contending with the use of these systems is one of the biggest challenges currently faced by medical professionals – because there’s no concrete way to test them without endangering human lives.









