The flood did not stop the flooding of investigative exposés on dataveillance, users in the United States seem more enmeshed than ever in those infrastructures, as if they are responding with a collective shrug—“I know, but all the same.” It’s not just naivete on the part of users; it’s more accurate to think of big data as something that we notice but that we don’t really remark on. For an end user still registers—if peripherally—the fact that one is being profiled. This isn’t always an explicit awareness, though that can certainly happen when apps such as TikTok highlight how good their algorithms are at serving up content personalized for you. In the main, though, personalization helps users feel “normal,” which is to say comfortable, included, and connected to a sense of social life. It is a welcoming invitation to ourselves, even though it may be intense. “Feeling normal” helps explain why we identify with digital platforms even when we know they have the potential to harm us.
Normality is often viewed as a negative when describing media. It refers to the feeling that mass audiences have lost their sense of individuality, and shed their ability for judgement. This concern is a long-standing one: “They all surrender to American tastes, they conform, they become uniform,” wrote one German publisher in 1926 about the effects of the American film industry on German audiences. In this sense, “normalcy” suggests a kind of discipline: People must conduct themselves according to preset norms of behavior rather than being authentic. Indeed, libertarians who scoff at “normies” and “sheeple” sometimes use normalcy as a hack, as a way of blending in to disguise one’s true intentions. Popular “Gray Man theory” sites offer advice on what to wear to disappear into a crowd when planning for a breakdown in civil society: “natural and neutral colors work best; browns and grays. Nothing to create a memory like a T-shirt with a saying or photos … Ordinary is the key word here.” (Of course, to pass as normal assumes a kind of privilege; some subjects—persons with disabilities and persons of color—have already been marked, sometimes violently, outside of the norm.) Similarly, web browser plug-ins such as TrackMeNot obfuscate your search terms by spewing out a cloud of more normal-seeming search patterns gleaned from other users online—for instance, “Living fulfilling lives without; that have been lost; make friends with your; must push back against; jaundiced newborns without additional.”
Because “normal” explains how the individual fits into the broader public, it does important work in digital culture. In an earlier era of mass media, television shows supplied scripts and narratives for living, such as homeownership or a nuclear family, that many audiences recognized as comfortingly close to their own, “normal” lives. While the era of three or four TV channels is long gone, we still desire that era’s sense of being adjacent to other people—and so the invitation to “feel normal,” despite these connotations of blandness, helps us navigate the state of being simultaneously private and public online. It’s a confusing space, where we are unsure how many other people are in the room with us, and where each pic seems like it might potentially reach millions—or nobody.
Websites attempt to solve this problem by conjuring up ghostly footprints of other nearby people. A travel website such as Expedia, for example, will inform you that “10 other people are looking at this hotel,” even though it is almost impossible to ensure those 10 other people are really online and looking at the same thing at the same time. Although this notice may seem like a nakedly consumerist tactic to encourage you to book the hotel and create artificial competition, it can also be an interesting way to instill a sense co-presence by suggesting you are connected with others.
Personalization tends to be subtler. Personalization attempts to identify and place you in the context of other people who have similar interests, so you don’t feel lost. Data broker Experian’s Mosaic product for digital advertisers, for example, has around 70 discreetly named market segments for each country it operates in, such as America’s M44 “Red, White, and Bluegrass” and S69 “Urban Survivors,” or Britain’s N59, “Asian Heritage,” that act as proxies for race, ethnicity, family status, and income, and serve to re-create the “neighborhood” each household occupies. (At one point, when an airline data leak accidentally embedded a visitor’s Mosaic score inside a hidden part of the webpage, I discovered I was in segment G24, “ambitious singles,” people who in their description “carry rolled-up rubber mats to work, prepped to duck out at lunch for a yoga class.” Reader, I wish!) German: The literal translation of unheimlich (uncanny) is “not at home.” By inversion, big data tries to simulate the feeling of being at home: comfortable, among your people and your things, even if this effort is so often riddled with failure. The promise of personalization means that the web is about you and not others; you are special, not common.
Problem is the real one isn’t personalization’s goal of getting you to feel normal; there isn’t anything wrong with a sense of belonging online. It’s the way that personalization pushes us to pursue our “authentic” selves. Personalization is only effective if people are motivated by their own interests. They must identify with their emotions, preferences and affinities so the algorithm can find other consumers and products that align with those values. Authenticity—or, as one popular T-shirt puts it, “f*ck the norm and be yourself”—is often a false feeling of uniqueness that is generated by an algorithm.