Nonbinary and transgender identities are increasingly being accepted and normalized throughout society, but not when it comes to high-tech facial recognition software developed by some of the largest tech firms in the world.
According to Forbes, a recent study by the University of Colorado, Boulder, found that when it comes to transgender and nonbinary people, facial recognition software misidentifies transgender people about a third of the time and always gets it wrongΒ when it comes to nonbinary folks, those who identify as neither male nor female.
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The issue is that while society is increasing its vocabulary when it comes to identifying and labeling gender, computer programs are still binary in their design.
βTraining a system to recognize gender beyond the binary breaks the purpose of the system,β Morgan Klaus Scheuerman, lead author of the study, told the Daily Camera. βIf someone wants to include nonbinary identities in their algorithm, the problem becomes that nonbinary people look like any other people, so the system wonβt know how to classify anyone.β
Scheuerman noted that systemsβ typical use of βcontextual labels,β like whether someone was wearing a dress or had long hair, to determine gender indicated that βtraditional concepts of gender are ingrained in facial recognition algorithms,β as the Daily Camera explains.
And so far, according to Scheuerman, a common response, if any, by tech companies has been to remove any classification of gender by their facial recognition algorithms, rather than try to teach them nonbinary concepts regarding gender.
Said Scheuermanβs co-author Jed Brubaker in a statement, per Forbes:
βWe knew there were inherent biases in these systems around race and ethnicity and we suspected there would also be problems around gender. Bottom line: What we found is that the computer vision systems that run all of our facial detection and facial analysis do not handle the level of gender diversity that we live with every day.β
Of course, as Daily Camera notes, removing all binary gender classifications from such systems is not necessarily prudent, given their usefulness in certain urgent tasks like locating a missing child.
But the slow adaptation of such crucial technology to be gender-nonconforming is frustrating for the LGBTQiA+ community, Mardi Moore, executive director of Coloradoβs Out Boulder County organization, told Daily Camera.
βThis kind of stereotyping flies in the face of what we know to be true about humans,β Moore said. βIt doesnβt reflect the real world.β
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