Arsenii Alenichev typed sentences like "Black African doctors providing care for white suffering children" and "Traditional African healer is helping poor and sick white children" into an artificial intelligence program designed to generate photo-like images.
His goal was to see if AI would come up with images that flip the stereotype of "white saviors or the suffering Black kids," he says. "We wanted to invert your typical global health tropes."
Alenichev is quick to point out that he wasn't designing a rigorous study. A social scientist and postdoctoral fellow with the Oxford-Johns Hopkins Global Infectious Disease Ethics Collaborative, he's one of many researchers playing with AI image generators to see how they work.
Alenichev's work is part of a broader study of global health images that he is conducting with his adviser, Oxford sociologist ...
NEW YORK (AP) — Matt Walker couldn’t pet a dog without sneezing — until he and other scientists used a gene editing technique to produce a hypoallergenic beagle named Bailey.
By Jessica Hamzelou, MIT Technology Review | 07.23.2026
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