Biases built into artificial intelligence may color even its ability to recognize simple household objects, according to a new study from Facebook researchers.
The report found that major computer vision systems tended to identify everyday items commonly found in lower-income communities and emerging-market countries with less accuracy than those from more economically advantaged areas. Researchers attributed the biases to geographic concentration, primarily English-language labelling and uniform cultural sensibilities found within public image datasets on which much of the technology is trained.
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