But consider the potential ramifications: if, for example, Google frequently coded women who worked in technology in 2012 as men, then it could have skewed data about the readership of tech publications to look more male than it actually was. People who run media sites pay close attention to their audience data, and use it to make decisions. If they believed their audiences were more male than they were, they might think, “Well, maybe women do just care less about technology”—an argument they’ve no doubt heard before. That might skew publications’ reporting on the gender gap in tech companies
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