Machine learning classifiers are up to 20% less accurate when labeling photos from homes in poor countries

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Added by Martin on 2019-06-17 11:56

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Creator(s): Cory Doctorow

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A new study from Facebook AI Research evaluates common machine-learning classifiers' ability to label photos of objects found in households in rich countries versus household objects from poor countries and finds that the models' performance lags significantly when being asked to classify the possessions of poor people. Partly that's due to differences in the objects…

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Machine learning classifiers are up to 20% less accurate when labeling photos from homes in poor countries A new study from Facebook AI Research evaluates common machine-learning classifiers' ability to label photos of objects found in households in rich countries versus household objects from poor countries and finds that the models' performance lags significantly when being asked to classify the possessions of poor people. Partly that's due to differences in the objects… Cory Doctorow