Despite the flood 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. This often-inchoate feeling, as intense as it can sometimes be, barely registers as any particular emotion at all, because it feels like a gentle invitation to be ourselves.
“Feeling normal” helps explain why we identify with digital platforms even when we know they have the potential to harm us. Buy This Book At: If you buy something using links in our stories, we may earn a commission. This helps support our journalism.
Learn more . When describing media, being normal is almost always seen as a negative, a sense that a mass audience has lost a sense of individuality and given up their capacity for judgment. 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. Some websites try to resolve this confusion by conjuring the ghostly traces of others nearby. 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.
That notice is, of course, a nakedly consumerist way of manufacturing artificial scarcity and competition to spur you into booking the hotel, but it is also a fascinating way of manufacturing a sense of co-presence, of suggesting that you are connected to others. Mostly, though, personalization tries to be more subtle. It attempts to recognize and situate you within the larger context of others who share your interests so that you never feel out of place.
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!) In 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. And so the very promise of personalization is that the web is all about you, not everyone else; that you are unique, not normal. The real problem 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 only works if we become self-interested, identifying with our emotions, our likes and dislikes, our preferences, and our affinities, so that the algorithm can return other people and consumer products that fit those affinities. 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.
But the idea that we even have authentic selves is a relatively recent phenomenon of modernity. Freud and other psychoanalysts laid the groundwork for a model of selfhood in which conflicting drives and fantasies constituted the “I,” and the sociologist Eva Illouz has shown that this model became part of what she calls “emotional capitalism,” which began to cement itself in the Western workplace in the half century after the 1920s. Attempting to help workers better communicate by registering and managing emotional states, workplace management theories drew upon the relatively new science of psychology.
They held that an “authentic self” that is normally hidden from consciousness could be recovered; it could “apprehend itself through texts, classify and quantify itself, and present and perform it publicly” through technologies of analysis (whether therapeutic or, as Illouz argues, digital self-fashioning). Emotional capitalism is now one of the most noticeable features of social media platforms, which encourage us to classify our emotional reaction to a post through a limited set of responses to further capture our behavior: On a Facebook post, do you “like” it, or do you feel “love,” “haha,” “wow,” “sad,” or “angry”? (Similarly, for a sentiment-analysis bot, the more emojis you use in a post, the better: They are the quickest shortcut to figure out how you are feeling. ) In today’s age of big data, our past behavior serves as signals that suggest how we might act in the future and becomes a way of finding ourselves.
But the “user” isn’t a self; it’s a marketing ploy. It’s how digital capitalism gathers more information about us. If authenticity has become the only way to feel normal, then what feminist scholar Sara Ahmed calls “the requirement to identify with the universal that repudiates you” is often a cruel burden.
Consider when a platform forces a trans person to identify with a deadname to become an authentically “verified user”; or when credit scoring requires someone in debt to identify with an opaque data profile and, ultimately, a credit system that excludes them; or when employees of Uber are required to identify with their identity as Uber drivers, even as that platform exploits them. The violence here is not simply being forced into certain patterns of behavior or being encouraged to buy more products, but of making a certain form of “authentic” selfhood that we call the “user” stand in for ourselves. Lest this be understood as a natural chain of events, keep in mind that there are many other ways of constructing social algorithms.
A 2018 summer workshop in Amsterdam explored social networks, such as Mastodon, that allow a user to register multiple identities for each community one plays a part in, obviating the need for a single, “authentic” self. Alternatively, a developer could connect users based on mutual indifference rather than mutual affinity. As media theorist Wendy Chun suggests, mutual indifference might produce social networks that are organized less around intensities of emotion and other types of content designed to trigger strong reactions than ones that are de-intensified.
The result would be social networks that are a little less like a gated community where everyone is expected to hate the same things (e. g. Fox News or CNN) and a little more like a city where it is possible to walk by another person with disinterest—a social form organized mostly around the emoji 😐 rather than just ❤️ or 😠.
More radically, if personalization teaches us to be authentic, this is an equation that we could begin to unlearn. After all, “being yourself” is exhausting work sometimes; it can even be a job requirement, as everyone from Insta influencers to ride-share drivers will tell you. (In college discussion sections, I remember teachers often asking me to be myself—which meant “be more ethnic”—for otherwise all-white classrooms.
) We could start to forget the idea that we are the sole authors of our identity, that our individuality is more important than the (“normal”) people around us, and that we even have a single or authentic self. This is tremendously difficult work. Because these data technologies are so permissive—counting almost anything as allowable behavior—they hold out the promise that everyone is included, no matter their identity.
Those users who are uncomfortable with this universalism are caught in a double bind. If mass consumerism continually asked, “Don’t you want to be happy?” the equivalent of refusing this system is saying no to the question, “Don’t you want your own wants?” or, alternately, “Don’t you want to be yourself?” To say no can seem perverse, even self-sabotaging—but only if you’re measuring by the standard of authenticity that society has uncritically accepted. “Feeling normal” online exerts a pull because it glues together two very different things: the hyper-individualized user and the user’s demographic neighborhood.
In other words, big data gives me Main Character Syndrome: Everything revolves around me. But it also treats me as a demographic category: a middle-income consumer, living in a midsize city in the Midwest. Particularly because big data constantly recalculates and resynthesizes the population that a user is compared to from moment to moment—digital scholar John Cheney-Lippold gives the example of an algorithm deciding you are 60 percent African American, then, after a few more clicks, 80 percent—it must also shore up the sense that your behavior is part of a larger collective body.
When it succeeds, it says that no matter what you do and where you go and who you are, “you” are part of a community of people who think like you. It suggests that we are all in a global relationship with the rhythms of consumer demand, or news, or even other communities—a rhythm of enforced sociality that crowds out the ability to be asocial or alone. There’s nothing wrong with wanting to feel normal on the internet.
But there are ways of feeling normal that allow us the space not to be ourselves all the time. The authentic user—and all the straightening mechanisms contained within it—is one of the most ingrained if unquestioned building blocks of digital culture. If we try to escape it, it can feel that we are repudiating ourselves.
But it might be worth a try. Excerpted from Digital Lethargy: Dispatches From an Age of Disconnection by Tung-Hui Hu (MIT Press, 2022).
From: wired
URL: https://www.wired.com/story/psychology-data-surveillance-normality-personality/
