I was tweeting about Facebook’s recent “Year in Review” fiasco, where the algorithm they created was generating reviews that included some terrible memories—deaths of children, divorces, etc. My point in the tweet was that, while algorithms might (or might not) be a good tool for efectively serving up the right ad to the right user, they might not be the best way to create emotional content or connect on a human level.28
The incident that Albert cites, and which prompted him to speak out about the limits of algorithms, is the story of Eric Meyer and the “cruel algorithm” serving up a picture of his recently deceased daughter as part of Facebook’s “year in review” feature. For Eric Meyer and others experiencing these unwanted flashes of painful memories, algorithmically curated and repackaged content does not just materialize in helpful birthday reminders. It also lingers as insensitive reminders of the tragedies of life. Emerging at odd moments, these digitally mediated memories make you “raise your head in surprise or alarm at the uncanny sensation of a half-known influence” (Stewart, 2007: 60). More than anything, however, the incident made explicit for Albert “the most obvious thing about algorithms—they’re just machines.” What was obviously missing, says Albert, was the “human judgment that says, ‘You know, this guy probably doesn’t want to be reminded that his daughter died this year, so even though the post got tons of atention, I’ll leave it out’.” Indeed, algorithmic systems “judge individuals against a set of contrasting norms, without human discretion intervening or altering decisions” (Beer, 2013: 77).
Similarly, Ryan, a 21-year-old avid YouTube user, thinks that mechanical ways of trying to solve human problems and desires is where the algorithm hits its barrier. The problem with algorithms, Ryan suggests, is “that they are just based on trends and past behavior. It can’t predict for you in the future, it just assumes you are going to repeat everything you’ve done in the past.” Algorithms do not take into account that “people are unpredictable and like to try new things all the time,” he says.29 This is why Ryan loves people who put considerable efort into their YouTube channels—particularly, the semifamous YouTube celebrities he follows, who explicitly ask fans to contribute to their next videos. For Ryan, these YouTube celebrities are almost like “human algorithms,” making sure they give their audience what they want. Ryan thinks they are “more accurate than an automatic algorithm, because computer algorithms don’t really understand human preferences or traits like actual humans do.” This is precisely what Hayden seems to touch on when he claims that people are not a math problem: People are more complicated than an equation, more complex and unpredictable than what can be broken down into a few steps of instructions for a computer. In fact, Hayden thinks algorithms are fundamentally not that smart. They were not able, for example, to parse the fact that “views” means beautiful scenery, while it also happens to be the name of the rapper Drake’s newest album. So, when Hayden uses the hashtag “views” for all his recent images of sunsets and landscape pictures on Instagram, he is not interested in following a bunch of Drake fans, which an algorithm apparently suggested. What became apparent in many of the participants’ responses, then, is not just how algorithms are capable of misjudging humans but how they might not even be able to judge humans at all.
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