CODED BIAS
A researcher’s discovery that widely used AI programs fail to accurately recognize the faces of women and people of color leads her down an alarming rabbit hole with disturbing implications.
As a woman of color, MIT Media Lab researcher Joy Buolamwini already found it difficult to have a voice in an industry dominated by white men. But when a program she creates using an industry-standard facial recognition algorithm fails to recognize even her, Joy takes action. Shalini Kantayya’s disquieting CODED BIAS presents the undeniable truth that these powerful, unsupervised algorithms contain a deeply ingrained bias against many marginalized people, including (but not only) women, people of color, and people with disabilities. This inherent bias may be responsible for those annoying targeted ads online, but has also played a part in loss of jobs, denial of loans, wrongful imprisonment, and more. As more countries and megacorporations adopt artificial intelligence programs to collect and process billions upon billions of sets of data, Joy seeks out others who are trying to bring greater public awareness and legislative scrutiny to bias in artificial intelligence before “data is destiny” becomes not just a tech industry mantra, but a death sentence for millions.
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