Sampling bias: how a machine-learning beauty contest awarded nearly all prizes to whites

If you’ve read Cathy O’Neil’s Weapons of Math Destruction (you should, right NOW), then you know that machine learning can be a way to apply a deadly, nearly irrefutable veneer of objectivity to our worst, most biased practices. report this ad Here’s a telling example of exactly how that works in practice. Beauty.ai is a joint Microsoft/Nvidia/Youth Laboratories project that applied machine learning techniques to rank 600,000 user-submitted selfies for their beauty, and picked 44 finalists: six Asians, one dark-skinned person, and thirty-seven white people. Are whites just that hot? Nope. But the training data for “beauty” comes from profoundly biased institutions (the first Black Miss America was crowned in 1983). What’s more, the European-based project leads ended up disproportionately sourcing their selfies from other white Europeans. In other words,…


Link to Full Article: Sampling bias: how a machine-learning beauty contest awarded nearly all prizes to whites