“It’s important these inequalities are brought to our awareness because if AI [systems] are full of biases, they can be used in a way that reproduces health inequity, which is really problematic,” says KBaeroee
Biases in AI tools such as those used to detect signs of disease could exacerbate inequalities in health care.A lack of racial and gender diversity could be hindering the efforts of researchers working to improve the fairness of artificial intelligence tools in health care, such as those designed to detect disease from blood samples or imaging data.
“These findings are a reflection of what's happening in the research community at large,” says study co-author Leo Anthony Celi, a health informatician and clinical researcher at the Massachusetts Institute of Technology in BostonA lack of diversity is problematic, because it leads to biased data sets and algorithms that work best for white people from rich countries, he says.
“You want those sitting at the table to be representative of those disproportionately burdened by disease, who could benefit most from these technologies,” says Celi. For example, Black people are at greater risk than white people of developing severe COVID-19, but some AI tools used to calculate blood oxygen levels work more accurately for white people.
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