As a 76 year old Medicare beneficiary, I am frequently annoyed by the blatant ploys that medical care providers use to game the 'fee for services' system: notably scheduling unnecessary appointments and procedures.
Metz and Smith describe how this behavior could be enhanced by a dark side of the use of A.I. in health care, as A.I. image analysis technology spreads across medicine, and systems are developed that can detect diabetic retinopathy, as well as lung and brain diseases.
Similar forms of artificial intelligence are likely to move beyond hospitals into the computer systems used by health care regulators, billing companies and insurance providers. Just as A.I. will help doctors check your eyes, lungs and other organs, it will help insurance providers determine reimbursement payments and policy fees.
Ideally, such systems would improve the efficiency of the health care system. But they may carry unintended consequences, a group of researchers at Harvard and M.I.T. warns. In a paper published on Thursday in the journal Science, the researchers raise the prospect of “adversarial attacks” — manipulations that can change the behavior of A.I. systems using tiny pieces of digital data. By changing a few pixels on a lung scan, for instance, someone could fool an A.I. system into seeing an illness that is not really there, or not seeing one that is.
...doctors, hospitals and other organizations could manipulate the A.I. in billing or insurance software in an effort to maximize the money coming their way...If an insurance company uses A.I. to evaluate medical scans, for instance, a hospital could manipulate scans in an effort to boost payouts. If regulators build A.I. systems to evaluate new technology, device makers could alter images and other data in an effort to trick the system into granting regulatory approval.
In their paper, the researchers demonstrated that, by changing a small number of pixels in an image of a benign skin lesion, a diagnostic A.I system could be tricked into identifying the lesion as malignant. Simply rotating the image could also have the same effect, they found.
Small changes to written descriptions of a patient’s condition also could alter an A.I. diagnosis: “Alcohol abuse” could produce a different diagnosis than “alcohol dependence,” and “lumbago” could produce a different diagnosis than “back pain."
In turn, changing such diagnoses one way or another could readily benefit the insurers and health care agencies that ultimately profit from them. Once A.I. is deeply rooted in the health care system, the researchers argue, business will gradually adopt behavior that brings in the most money.
