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    Home»Opinions»What HBO’s ‘The Pitt’ gets wrong about AI — and what medicine misses
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    What HBO’s ‘The Pitt’ gets wrong about AI — and what medicine misses

    The Daily FuseBy The Daily FuseMarch 6, 2026No Comments5 Mins Read
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    What HBO’s ‘The Pitt’ gets wrong about AI — and what medicine misses
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    Generative synthetic intelligence has already reshaped industries akin to laptop programming, retail and manufacturing. In drugs, nonetheless, fears of scientific error have slowed adoption.

    At current, two-thirds of doctors report using GenAI tools in apply, although half insist that stronger safeguards are needed.

    This break up — between physicians desperate to undertake AI and people cautious of its dangers — took middle stage in a current episode of HBO’s “The Pitt,” set in a fictional Pittsburgh emergency division.

    Within the episode (titled “8:00 A.M.”), protagonist Dr. Michael “Robby” Robinavitch is a veteran emergency doctor cautious of recent expertise. Dr. Baran Al-Hashimi, his momentary alternative, is extra enthusiastic.

    She introduces an AI documentation instrument referred to as Ambient Listening to streamline charting. The applying saves time and impresses residents. Then it misidentifies a medicine, an error that would have had severe penalties had one other doctor not caught it.

    I’ve written extensively about generative AI’s influence on drugs and located the episode riveting. Whereas the present precisely captured the stress between AI’s advocates and skeptics in drugs, what it overlooked was much more important than what it portrayed.

    “The Pitt” appropriately depicts that many clinicians stay frightened of this highly effective, new expertise.

    Along with fears that AI will make a mistake that injures a affected person, docs additionally fear that it’s going to develop too highly effective, finally overriding scientific judgment and diminishing the doctor’s function. Each anxieties are affordable, and collectively they’ve slowed the adoption of generative AI.

    In most hospitals, generative AI has been restricted to administrative work: listening to affected person encounters, drafting notes for the digital medical file, summarizing charts, and aiding with billing and coding duties. Regardless of the hype, solely the most advanced health systems are deploying AI to assist docs and sufferers diagnose and develop therapy plans.

    In that sense, the present will get the central dynamic proper. Generative AI in drugs is neither universally embraced as good nor utterly dismissed as ineffective. As a substitute, it has been adopted cautiously in areas unlikely to have an effect on scientific outcomes.

    In a single scene, Dr. Al-Hashimi assures her colleagues that the AI system is “98% correct.” However with out context, that determine is deeply deceptive.

    Accuracy is determined by what’s being measured. If Al-Hashimi meant that AI avoids 98% of minor documentation errors, then that determine grossly overstates its efficiency. But when that statistic means AI makes harmful errors 2% of the time, there’s no proof to assist that assertion both.

    The episode’s greatest error is overstating human efficiency in comparison with technological outcomes. When Al-Hashimi tells her colleagues the expertise is “wonderful, however not good” and due to this fact should all the time be overseen by a human, she implies clinicians hardly ever make errors. That assumption is grossly inaccurate.

    Misdiagnoses contribute to almost 400,000 American deaths annually, with one other 250,000 fatalities linked to preventable medical errors. Research present that at the least half of electronic health records include at the least one mistake, and lots of are perpetuated when busy physicians copy and paste prior affected person notes.

    The important thing query isn’t whether or not generative AI is flawless. It’s whether or not it outperforms clinicians working alone. Even a modest drop in misdiagnoses and preventable hurt would save tens of 1000’s of lives annually.

    The episode focuses on present tensions with GenAI. What it omits is the place this expertise is headed.

    Already, in head-to-head diagnostic comparisons, generative AI performs at ranges akin to human clinicians.

    And as instruments enhance quickly, the talk will quickly shift. The query will now not be whether or not GenAI belongs in drugs, however the way to deploy it most successfully.

    Its biggest influence is unlikely to be in emergency rooms and hospitals. Will probably be in serving to to handle tens of hundreds of thousands of People dwelling with persistent illness.

    CDC information present that higher management of hypertension and diabetes might stop as much as half of coronary heart assaults, strokes and kidney failure. At the moment, sufferers with these diseases are seen just a few instances a 12 months, which helps clarify why hypertension is successfully managed in solely half of People. Diabetes management charges are even decrease.

    GenAI can analyze information from house blood strain cuffs, glucose displays and wearables, enabling earlier treatment changes and timelier therapies. As a substitute of ready for a affected person’s subsequent workplace appointment or disaster, clinicians will have the ability to intervene when warning indicators seem. Extra steady monitoring has allowed some U.S. well being programs to achieve control rates near 90%.

    Superior high quality at decrease prices is the specified future that “The Pitt” doesn’t discover. The central debate going ahead is not going to be docs versus machines. Will probably be how docs and expertise accomplice for the good thing about sufferers. In the end, the mix of devoted clinicians, empowered sufferers and generative AI will yield scientific outcomes exponentially higher than any one of many three alone.

    Robert Pearl, the writer of “ChatGPT, MD,” teaches at each the Stanford College College of Medication and the Stanford Graduate College of Enterprise. He’s a former CEO of The Permanente Medical Group.



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