In case you’ve been on TikTok recently, you may have come face-to-face with a scarily yassified version of yourself. The Daring Glamour TikTok filter, which has now been utilized in 46.8 million videos, is a heavy contour make-up filter that changes in response to who’s using it, and never glitches. It is only one example of the brand new generation of filters which use AI and machine learning to be eerily lifelike and undetectable. Others include the Teenage Look filter, which de-ages users, and the Lite Foundation filter, which removes moles, beauty marks and pimples spots, giving people an unnervingly unblemished facade. 

Unlike cookie-cutter AR filters that overlay a one-size-fits-all effect onto a face, the technology that’s believed to be utilized in these newer filters – Generative Adversarial Networks (GAN) – is machine-deep learning tech that regenerates every pixel on a face based on a dataset of images. (TikTok’s parent company, ByteDance, hasn’t revealed the precise technology behind these latest filters, but many filter creators, technologists and users have speculated this.) Individuals who have used Daring Glamour noticed it modified in response to different hair colors, applied kind of make-up based on how masculine or feminine it deemed one’s bone structure, and altered in real-time based on whether or not they were hiding their eyebrows or not. 

“AR filters are like watching an old movie with outdated computer graphics – you understand it’s not real,” says Daniela Gustafson, 27, an Atlanta, Georgia-based beauty enthusiast, who posted a TikTok recently demonstrating how the Lite Foundation filter removes her mole, pixel by pixel. “But just with how computer graphics improved in film, so do the filters on TikTok.” Since Snapchat first introduced AR filters in 2015, we’ve seen them evolve from puppy filters and flower crowns to something more insidious. Many set a latest unreachable beauty standard, perpetuating colourism and Eurocentric ideals. The result has been unprecedented surges in cosmetic surgery and cosmetic procedures, and a subsequent global mental health crisis. Experts warn that the realistic nature of this latest generation of filters poses other threats, which can only compound current issues.

Early Education Specialist Rory Gascoigne tells me over the phone that, in accordance with a latest theory in neuroscience often called predictive processing, our brains make sense of the world by predicting what we are going to see after which updating these predictions as a situation changes. Our brains construct predictive models about every part. For instance, as a baby, people construct predictive models concerning the laws of physics by bouncing a ball against the bottom. This permits us to interact with the world around us successfully and anticipate future occurrences from patterns. 

“The brain’s primary focus is to avoid prediction errors,” he explains. When prediction errors occur, we struggle to understand the difference between reality and our perception of reality. “It’s very just like how eating disorders manifest. Someone can have an internal model that sees themselves as fat. So they appear within the mirror, and that is what they see, regardless that they could be anorexic since the brain is in a position to gloss over the small print that your mind doesn’t wish to see.”

Similarly, in the event you spend enough time using filters like Daring Glamour, chances are you’ll begin to develop a predictive model of yourself where your brain thinks you appear like that. If you see your actual face in real life or in photos, your brain will experience a prediction error that isn’t just viscerally uncomfortable but can result in mental health issues, resembling dysmorphia or depression. “Your brain is continually engaged within the strategy of creating feedback loops with the environment where you construct a model of reality,” he explains. “So in the event you start having an idea of yourself that shifts your reality in a single direction or the opposite, you start to behave in ways in which seek validation for that reality.” Which may include only ever sharing photos of yourself using filters or going so far as emulating your filtered self in real life. 

Gascoigne points to the instance of how before filters, people brought photos of celebrities right into a plastic surgeon’s office. Now they carry in filtered images of themselves. “This happens because they’re beginning to construct this internal model that states that that is the one valid method to look. Once they see themselves without the filter, they’re getting further and further and further away from something that matches their reality.”

He isn’t sure what the final word results of this might be but says “the extent to which these filters are utilized by young people at a time of their life after they are first constructing these models of self-identity is worrying. In the event that they’re corrupted to think that they need to appear like a filter, that’s setting them up for a difficult time in life.” This cognitive dissonance between what we predict we should always appear like and what we actually appear like positions people to be stuck in a loop of hopelessness and feelings of failure.

TikTok creator Laura Gouillon leverages her background in computer science, creative direction and film to create viral filters. She has revamped 100 effects on TikTok, garnering over 11.4 billion views worldwide. Gouillon is happy by the technological advancements we’re witnessing and doesn’t think the technology itself is necessarily dangerous. “I feel the challenge for existing and future social media platforms might be providing context on the presence of photo and video manipulation,” she says, “in an effort to cut back the potential negative psychological impact on users.”

But are disclaimers about who’s using a filter adequate? France seems to hope so: this month the country’s lower chamber passed a bill to make it mandatory for influencers to label when images use filters or Photoshop. In a Dazed article, nevertheless, beauty culture critic Jessica DeFino posited that transparency isn’t a net positive, pointing to a study which found Photoshop transparency on promoting and marketing images was ineffective.

At the top of March, leaders in AI raised grave concerns concerning the rate at which AI is developing. In an open letter with greater than 1,100 signatories – including Elon Musk, Apple co-founder Steve Wozniak, and Skype co-founder Jaan Tallinn – they called for a moratorium on state-of-the-art AI development. They warned that “AI systems with human-competitive intelligence can pose profound risks to society and humanity”.

“I’m fearful that with such great advances with machine learning filters, we is perhaps headed towards a proliferation of deep fakes where users will give you the option to ‘wear’ the digital face of one other person in a hyper-realistic way, which might make it harder to combat catfishing and disinformation,” says Maria Thuý Hiên Than, who’s a filter creator, creative technologist, and activist. 

Despite these fears, nevertheless, Gascoigne assures me that there’s some hope. “The AI itself is neutral. How we use it as a social or cultural artefact causes the issues.” Thus to make use of it properly, we must first destroy our biases, conquer patriarchal beliefs about what and who is gorgeous, and eradicate the white supremacy etched into the use cases of our technology. 

For Than the answer to combating this is easier than ridding the world of prejudice – it’s human creativity. “I would like to see the crazy shit,” she tells me. “I do know some individuals are already using generative AI to take a look at more creative, ethereal, and imaginative applications of AI filters, I would like to see more of that. The more tech advances, the more technical boundaries we’re breaking, and which might be pushing us to think outside of the box visually, and that’s what’s so exciting about this all.”

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