The Falsifications of Face Filters
Face filters. We’ve all seen them, we’ve all tried them. We’ve also all seen what they do to our faces, the way they narrow our noses and enlarge our eyes and sometimes even whiten our skin. Augmented reality face filters, especially the deliberately clownish ones, can be a simple way to have some harmless fun and share a laugh with friends. But if you’re like 50% of adolescent girls, the ubiquity of face filters can make you believe that your real, unfiltered face is defective and that you don’t look good enough without photo editing. That’s one in every two. One in every two girls who have been so inundated with airbrushed selfies and filtered photos of celebrities, influencers, peers, and their own faces that their confidence and self-esteem have plummeted and they feel that they can’t look beautiful if they aren’t digitally enhanced and flawless. The harmful messaging that face filters spread and the consequent effects of this messaging on society far outweigh any sort of benefit people may derive from them.
If you examine how face filters meant to “beautify” alter our faces, you’ll see that the tweaks they make are far from random. Jameela Jamil, British actress, model, and passionate advocate of many causes including body neutrality, has explained in an interview with Harper’s Bazaar that Instagram is overpopulated by “the same kind of doll face, the tiny, tiny, contoured nose, massive lips, big slanted eyes: general Eurocentric beauty but with aspects of different ethnicities that we deem acceptable. But we won’t accept the people from those ethnicities: instead, we turn white faces into combinations of them.” Jamil’s observations, plus the way that many filters are programmed to lighten skin tone, slim down faces and bodies, narrow waists, remove wrinkles, and more shows that these tools are racialized, gendered, aged, classed, abled, and normative. They implicitly communicate what kinds of faces and bodies are worthy and unworthy of being digitally displayed.
And who exactly gets to decide that worthiness? The creators who design face filters, the demographic of which is certainly not nearly as diverse as the demographic of people who use them. This group of people — most likely men, mostly likely white — are informed by their own specific ideas and biases of what counts as “beautiful,” which are then imposed and superimposed onto the minds and faces of innumerable people of all ages, races, genders, ability, and appearances. In Chapter 1 of Data Feminism, Catherine D’Ignazio and Lauren Klein explain that there are forces of oppression that are “so baked into our daily lives — and into our datasets, our databases, and our algorithms — that we often don’t even see them.” We don’t often recognize the ageism buried in the way face filters blur out wrinkles, the Eurocentrism in the way they narrow down noses. These biases are so deeply ingrained in the mindsets of face filter creators and AR technologists that they often don’t recognize it themselves, and these subconscious biases are what inform the designs of the face filters that are applied to millions of faces around the world. That means millions of uniquely formed facial features, skin tones, bone structures, and other aspects of individuality are rearranged to conform to (or at least more closely resemble) the highly specific visions of beauty of a very select few, and there is no way that that is not problematic.
The influence of face filters is not only superficially widespread, but it is also deep-seated. Every time a user comes across another picture or post of a filtered face, it adds another layer of plausibility to the damaging illusion that the flawlessness they portray is achievable and the norm. Unobtrusive face filters can act as automated facial retouching, making it impossible to tell whether a photo uploaded on social media has been edited or not, setting unrealistic and unattainable beauty standards and expectations for users, especially younger ones who are more impressionable. Face filters can also exacerbate the insecurities and distorted self-images of users in ways that other forms of edited imagery do not, as they cause users to not only compare themselves to the airbrushed appearances of celebrities and influencers, but to compare their real appearances against their own airbrushed faces. This can cause them to unfairly and unhealthily compare their real faces against an impossible version of themselves and severely impair their self-esteem.
It first came into my awareness that this was a problem when I saw how face filters affected my friend Ruby. She and I were hanging out at a friend’s house one afternoon, sitting on the couch together, and I was watching her go through her Snapchat and send all her streak snaps. After watching her for a while, something clicked in my brain and I finally noticed the ongoing pattern that every single selfie and video Ruby took on the app had face filters over them. Even the casual daily streaks snaps she was sending her close friends were overlaid with beauty filters, not to mention the photos and videos she posted on her stories, both the public and private ones. She seemed to be partial to ones that enlarged her eyes and shrank her nose and jaw, which in hindsight were probably the parts of her face she was insecure about. What concerned me most was the fact that Ruby was using face filters to check her face the way one checks a mirror. I watched as she opened Snapchat on her phone and used its camera to fix her hair and examine her face, all while keeping a filter on. I was given the impression that she would be unable or at least unwilling to look at herself without a protective layer of AR technology modifying her face, and her behavior pointed to the presumption that she was in denial of what her face actually looked like.
Ruby’s situation is not the only unfortunate condition that can arise from the widespread prevalence of face filters. The availability and accessibility of filters make it easy for users to only photograph their faces using them much like Ruby did, and this can lead to distorted perceptions of what one should look like. This effect can be more potent with augmented reality filters than its photo counterpart called “selfie dysmorphia,” as the modification is more realistic and happens in real time. When this phenomenon reaches an extreme, it can become something often dubbed “Snapchat dysmorphia,” which is a growing phenomenon where social media users seek cosmetic surgeries and procedures inspired and guided by social media filters and editing apps in order to look more like their own filtered selfies. These procedures include those that remove dark circles, alter the shape of eyebrows, and reduce the size of pores in order to create an airbrushed effect. Other common filter-based surgeries include “rhinoplasty, blepharoplasty, chin augmentation, submental liposuction or facelift surgery,” some of which are pretty invasive procedures. The term Snapchat dysmorphia is related to a mental health condition called body dysmorphic disorder (BDD), where one is obsessively focused on at least one perceived, slight, or nonexistent flaw in their physical appearance. BDD interferes with individuals’ day to day functioning as those suffering from it experience emotional distress and can spend hours fixating on their minor flaws. This condition affects one in 50 people in the United States, and seeing that Snapchat has 200 million active users who view or engage with its filters every day, Snapchat dysmorphia undoubtedly probably affects a significant portion of the population as well.
Some people think that face filters are a fun, harmless, even beneficial tool that can make selfies look more interesting and presentable and attractive. They compare using face filters to getting professional headshots retouched, and say that filters are just a quick and simple way to cover small blemishes. Those who argue that face filters are beneficial often refer to the boost in confidence it can afford to users and believe that face filters do no harm as they make users feel more confident in how they look without bringing any injury to others. They posit that there is nothing wrong with wanting to look your best and feel confident, especially since the person who cares the most about how someone looks is that person themself.
But what these people are forgetting is that this boost in confidence is artificial and comes at a very steep cost. The pervasiveness and convenience of face filters makes it easy for users to grow dependent, even overdependent on them, the flawlessness they push gradually chipping away at users’ self-image until their confidence collapses. Face filters may have some perks, but whatever merit they may have is heavily overpowered by their detrimental drawbacks.
