We voluntarily produce floods of data on sites that exploit our identities and preferences for profit. It’s no wonder algorithm systems make many feel uneasy.
Late last year, Valerie Peter, a twenty-three-year-old student in Manchester, England, realized that she had an online-shopping problem. It was more about what she was buying than how much. A fashion trend of fuzzy leg warmers had infiltrated Peter’s social-media feeds—her TikTok For You tab, her Instagram Explore page, her Pinterest recommendations.
Peter’s dilemma brought to my mind a term that has been used, in recent years, to describe the modern Internet user’s feeling that she must constantly contend with machine estimations of her desires: algorithmic anxiety. Besieged by automated recommendations, we are left to guess exactly how they are influencing us, feeling in some moments misperceived or misled and in other moments clocked with eerie precision. At times, the computer sometimes seems more in control of our choices than we are.
Almost every other major Internet platform makes use of some form of algorithmic recommendation. Google Maps calculates driving routes using unspecified variables, including predicted traffic patterns and fuel efficiency, rerouting us mid-journey in ways that may be more convenient or may lead us astray. The food-delivery app Seamless front-loads menu items that it predicts you might like based on your recent ordering habits, the time of day, and what is “popular near you.
The Airbnb hosts’ concerns were rooted in the challenges of selling a product online, but I’m most interested in the similar feelings that plague those, like Valerie Peter, who are trying to figure out what to consume. To that end, I recently sent out a survey about algorithms to my online friends and followers; the responses I received, from more than a hundred people, formed a catalogue of algorithmic anxieties.
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