Teaching computers to understand human language used to be a tedious and imprecise process. Now, language algorithms analyze oceans of text to teach themselves how language works. The results can be unsettling, such as when the Microsoft bot Tay taught itself to be racist after a single day of exposure to humans on Twitter.
It turns out that data-fueled algorithms are no better than humans—and frequently, they’re worse.
“Data and datasets are not objective; they are creations of human design,” writes data researcher Kate Crawford. When designers miss or ignore the imprint of biased data on their models, the result is what Crawford calls a “signal problem,” where “data are assumed to accurately reflect the social world, but there are significant gaps, with little or no signal coming from particular communities.”
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Source: Algorithms Have Nearly Mastered Human Language. Why Can’t They Stop Being Sexist? – VICE