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A research team from MIT and Harvard published in the medical journalThe Lancet Digital Healthpublished an article in , saying that an AI program can tell a patient’s ethnicity from X-ray and CT scan results,Accuracy up to 90%.

This is not good news becauseScientists haven’t figured out how these AI programs can tell races.

“When my graduate students showed me some of the results in this paper, I thought it must have gone wrong,” MIT assistant professor Marzyeh Ghassemi, one of the authors of the paper who analyzed the corresponding topic, told the media. When they told me, I really thought my students were crazy.”

Marzyeh Ghassemi

▲ Marzyeh Ghassemi

As mentioned in this article, AI diagnostic systems seem toDiagnose and treat patients based on race, rather than the patient’s individual physical condition. This practice will harm the patient’s health.

The researchers mentioned a case where an AI program, while examining a chest X-ray,Higher odds of missing physical lesions in black and female patients.

The purpose of this research is to confirm the extent to which AI systems can detect human race from medical images, and how they can detect race information from it.

To do this, the research team trained the AI ​​system using medical images of different parts of the human body. The medical images fed to the AI ​​system did not contain obvious ethnic markers such as hair texture, skin color, and BMI or bone density.

Through testing, the researchers found that,The AI ​​system can identify the human race with an accuracy rate of up to 90%. The AI ​​system can identify ethnicity from medical images of any body part.

Even more surprising is thatAI system can accurately identify ethnicity from even severely missing or damaged medical images.

What researchers are more concerned with is not the fact that AI systems can detect human race per se, but that the clinical performance of AI systems will be affected by these racial biases. And doctors may ignore errors in the AI ​​system’s diagnostic results.

“The ability of AI to predict racial identity is not inherently important, but this ability is likely to be present in many medical imaging analysis models, which will exacerbate the problem of racial disparities already in the clinic,” the authors said.

Humans are currently unable to confirm which features of medical images an AI system detects a patient’s ethnicity, and the AI’s ability to identify a patient’s ethnicity from medical images of any part of the body, as well as severely damaged medical images, means using medical imaging technology to create An AI system without racial bias would be very difficult.

Ghassemi told the media that she speculated that perhaps the medical images were recorded in some unknown wayThe level of melanin in the patient’s skinso as to be recognized by the AI ​​system.

According to the research results,It is also possible that there are some innate differences between races.

Alan Goodman, a professor of biological anthropology at Hampshire College and one of the authors of “Racism Is Not Race,” told the outlet he doesn’t quite agree with that statement.

Alan Goodman

▲ Alan Goodman

In previous studies, scientists have struggled to find consistent racial differences in the human genome, but they have often been able to find consistent genetic differences based on the evolution of human ancestors. Therefore, genetic differences between people are more likely to be due to different characteristics of the evolution of individual human ancestors, rather than race.

Ghassemi said,More research is needed on this issue to draw firm conclusions.

“We need to put AI systems on hold,” said MIT scientist and physician Leo Anthony Celi. “We can’t rush into hospitals and clinics until we can confirm that AI systems are not making racist or sexist decisions. .”

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