Recommendations based on user preferences often reflect the biases of the world—in this case, the diversity problems that have long been apparent in media and modeling. Those biases have in turn shaped the world of online influencers, so that many of the most popular images are, by default, of people with lighter skin. An algorithm that interprets your behavior inside such a filter bubble might assume that you dislike people with darker skin. And it gets worse: recommendation algorithms are also known to have an anchoring effect, in which their output reinforces users’ unconscious biases and can even change their preferences over time.
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