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    Home » What using artificial intelligence to help monitor surgery can teach us
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    What using artificial intelligence to help monitor surgery can teach us

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    What using artificial intelligence to help monitor surgery can teach us
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    Teodor Grantcharov, a professor of surgery at Stanford, thinks he has discovered a device to make surgery safer and reduce human error: AI-powered “black boxes” in working theaters that work in an analogous means to an airplane’s black field. These gadgets, constructed by Grantcharov’s firm Surgical Safety Technologies, file the whole lot within the working room by way of panoramic cameras, microphones within the ceiling, and anesthesia screens earlier than using artificial intelligence to help surgeons make sense of the info. They seize your entire working room as an entire, from the variety of occasions the door is opened to what number of non-case-related conversations happen throughout an operation.

    These black bins are in use in nearly 40 establishments within the US, Canada, and Western Europe, from Mount Sinai to Duke to the Mayo Clinic. But are hospitals on the cusp of a brand new period of security—or creating an setting of confusion and paranoia? Read the total story by Simar Bajaj right here. 

    This resonated with me as a narrative with broader implications. Organizations in all sectors are enthusiastic about how to undertake AI to make issues safer or extra environment friendly. What this instance from hospitals reveals is that the state of affairs isn’t at all times clear minimize, and there are numerous pitfalls you want to keep away from. 

    Here are three classes about AI adoption that I discovered from this story: 

    1. Privacy is essential, however not at all times assured. Grantcharov realized in a short time that the one means to get surgeons to use the black field was to make them really feel shielded from doable repercussions. He has designed the system to file actions however conceal the identities of each sufferers and employees, even deleting all recordings inside 30 days. His concept is that no particular person needs to be punished for making a mistake. 

    The black bins render every particular person within the recording nameless; an algorithm distorts folks’s voices and blurs out their faces, reworking them into shadowy, noir-like figures. So even when you understand what occurred, you can’t use it in opposition to a person. 

    But this course of isn’t excellent. Before 30-day-old recordings are routinely deleted, hospital directors can nonetheless see the working room quantity, the time of the operation, and the affected person’s medical file quantity, so even when personnel are technically de-identified, they aren’t really nameless. The result’s a way that “Big Brother is watching,” says Christopher Mantyh, vice chair of scientific operations at Duke University Hospital, which has black bins in seven working rooms.

    2. You can’t undertake new applied sciences with out profitable folks over first. People are sometimes justifiably suspicious of the brand new instruments, and the system’s flaws when it comes to privateness are a part of why employees have been hesitant to embrace it. Many medical doctors and nurses actively boycotted the brand new surveillance instruments. In one hospital, the cameras have been sabotaged by being circled or intentionally unplugged. Some surgeons and employees refused to work in rooms the place they have been in place.

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