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A doctor can’t tell if somebody is Black, Asian, or white, just by looking at their X-rays. But a computer can, according to a surprising new paper by an international team of scientists, including researchers at the Massachusetts Institute of Technology and Harvard Medical School.
The study found that an artificial intelligence program trained to read X-rays and CT scans could predict a person’s race with 90 percent accuracy. But the scientists who conducted the study say they have no idea how the computer figures it out.
“When my graduate students showed me some of the results that were in this paper, I actually thought it must be a mistake,” said Marzyeh Ghassemi, an MIT assistant professor of electrical engineering and computer science, and coauthor of the paper, which was published Wednesday in the medical journal The Lancet Digital Health. “I honestly thought my students were crazy when they told me.”
At a time when AI software is increasingly used to help doctors make diagnostic decisions, the research raises the unsettling prospect that AI-based diagnostic systems could unintentionally generate racially biased results. For example, an AI (with access to X-rays) could automatically recommend a particular course of treatment for all Black patients, whether or not it’s best for a specific person. Meanwhile, the patient’s human physician wouldn’t know that the AI based its diagnosis on racial data.
The research effort was born when the scientists noticed that an AI program for examining chest X-rays was more likely to miss signs of illness in Black patients. “We asked ourselves, how can that be if computers cannot tell the race of a person?” said Leo Anthony Celi, another coauthor and an associate professor at Harvard Medical School.
The research team, which included scientists from the United States, Canada, Australia, and Taiwan, first trained an AI system using standard data sets of X-rays and CT scans, where each image was labeled with the person’s race. The images came from different parts of the body, including the chest, hand, and spine. The diagnostic images examined by the computer contained no obvious markers of race, like skin color or hair texture.
Once the software had been shown large numbers of race-labeled images, it was then shown different sets of unlabeled images. The program was able to identify the race of people in the images with remarkable accuracy, often well above 90 percent. Even when images from people of the same size or age or gender were analyzed, the AI accurately distinguished between Black and white patients.
But how? Ghassemi and her colleagues remain baffled, but she suspects it has something to do with melanin, the pigment that determines skin color. Perhaps X-rays and CT scanners detect the higher melanin content of darker skin, and embed this information in the digital image in some fashion that human users have never noticed before. It’ll take a lot more research to be sure.
www.bostonglobe.com
This is a follow-up study from this:
The study found that an artificial intelligence program trained to read X-rays and CT scans could predict a person’s race with 90 percent accuracy. But the scientists who conducted the study say they have no idea how the computer figures it out.
“When my graduate students showed me some of the results that were in this paper, I actually thought it must be a mistake,” said Marzyeh Ghassemi, an MIT assistant professor of electrical engineering and computer science, and coauthor of the paper, which was published Wednesday in the medical journal The Lancet Digital Health. “I honestly thought my students were crazy when they told me.”
At a time when AI software is increasingly used to help doctors make diagnostic decisions, the research raises the unsettling prospect that AI-based diagnostic systems could unintentionally generate racially biased results. For example, an AI (with access to X-rays) could automatically recommend a particular course of treatment for all Black patients, whether or not it’s best for a specific person. Meanwhile, the patient’s human physician wouldn’t know that the AI based its diagnosis on racial data.
The research effort was born when the scientists noticed that an AI program for examining chest X-rays was more likely to miss signs of illness in Black patients. “We asked ourselves, how can that be if computers cannot tell the race of a person?” said Leo Anthony Celi, another coauthor and an associate professor at Harvard Medical School.
The research team, which included scientists from the United States, Canada, Australia, and Taiwan, first trained an AI system using standard data sets of X-rays and CT scans, where each image was labeled with the person’s race. The images came from different parts of the body, including the chest, hand, and spine. The diagnostic images examined by the computer contained no obvious markers of race, like skin color or hair texture.
Once the software had been shown large numbers of race-labeled images, it was then shown different sets of unlabeled images. The program was able to identify the race of people in the images with remarkable accuracy, often well above 90 percent. Even when images from people of the same size or age or gender were analyzed, the AI accurately distinguished between Black and white patients.
But how? Ghassemi and her colleagues remain baffled, but she suspects it has something to do with melanin, the pigment that determines skin color. Perhaps X-rays and CT scanners detect the higher melanin content of darker skin, and embed this information in the digital image in some fashion that human users have never noticed before. It’ll take a lot more research to be sure.
MIT, Harvard scientists find AI can recognize race from X-rays — and nobody knows how - The Boston Globe
As artificial intelligence is increasingly used to help make diagnostic decisions, the research raises the unsettling prospect that AI-based health systems could generate racially biased results.
www.bostonglobe.com
This is a follow-up study from this:
Technology - AI models still racist, even with more balanced training
AI algorithms can still come loaded with racial bias, even if they're trained on data more representative of different ethnic groups, according to new research. An international team of researchers analyzed how accurate algorithms were at predicting various cognitive behaviors and health...
www.thehelper.net
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