The Development of Augmented Reality Filters and How They Affect Online Communities
What is Augmented Reality?
Overlaying digital objects on top of real-world surroundings is known as augmented reality, or AR. AR filters, made popular by apps like Instagram and Snapchat, alter facial features, apply effects, and produce completely new digital identities (Azuma, 1997).
From straightforward enhancements like dog ears or flower crowns, AR filters have evolved into sophisticated beauty filters that alter bone structure, smooth skin, and reshape facial features. Questions concerning digital identity and self-perception are brought up by these hyper-realistic changes.
AR Filters' Popularity on Social Media
AR filters have become more popular as a result of social media platforms, especially Instagram and Snapchat. Among the important figures are:
Of Instagram users, 46% have experimented with the filter effect.
Every day, 500 million people use Instagram Stories, and many of them use AR filters.
Every month, 700 million users interact with AR effects on various Meta platforms.
Filters are now instruments for identity experimentation and self-improvement rather than just amusement. Some criticise AR for reinforcing uniform beauty standards, while others contend that it fosters creativity (Miller & McIntyre, 2022).
Beauty filters and unrealistic ideals of beauty
Designed to "enhance" facial features by smoothing skin, enlarging lips, and reshaping noses, beauty filters are among the most widely used AR tools. A globalised, unattainable standard of beauty is a result of these changes, which frequently mirror Western beauty standards (Rettberg, 2014).
Exposure to beauty-enhancing filters on a regular basis can cause people to view their bodies as objects for evaluation, according to the Objectification Theory (Fredrickson & Roberts, 1997). Following extended use of filters, many users express dissatisfaction with their natural appearance, which can result in problems with self-esteem and heightened interest in cosmetic surgery (Rajanala, Maymone & Vashi, 2018).
Snapchat Dysmorphia and the Discussion of Mental Health
Snapchat dysmorphia, the practice of people seeking cosmetic surgery to look like their filtered selves, is becoming a bigger problem. Patients now show filtered selfies to plastic surgeons as reference images rather than celebrity photos (Burnell, Kurup & Underwood, 2021).
This phenomenon demonstrates a vicious cycle of body dissatisfaction and AR filter use:
According to Perloff (2014), users who use beauty filters internalise unrealistic expectations, feel dissatisfied with their actual appearance, and seek out additional digital or physical modifications. By flagging filtered photos, social media companies try to control extreme beauty modification, but algorithm-driven content recommendations still encourage unattainable beauty standards (Lawrence & Cambre, 2020).
The Authenticity Debate and the Digital-Forensic Gaze
A "digital-forensic gaze" has developed as AR filters make it harder to distinguish between digital enhancement and reality (Lawrence & Cambre, 2020). Users of social media now carefully examine photos for evidence of editing, frequently participating in online discussions about what is "real" and what is artificially created.
Because it promotes perfectionist standards, this forensic gaze can be problematicâeven photos that appear natural are examined for indications of enhancement. Self-presentation and the creation of digital identities are influenced by the paradox created by the pressure to remain authentic while still adhering to beauty standards.
AR Filters' Implications for Gender
AR filters are often coded as feminine technologies, focusing on beautification and self-enhancement. Research shows that:
Women use filters to align with beauty norms, reinforcing traditional gender expectations.
Men may avoid certain filters due to masculinity concerns, though humor-based and gaming-related AR tools are more widely accepted (Pescott, 2020).
Children as young as ten understand and internalize gendered filter use, indicating that beauty standards are learned early (Pescott, 2020).
These findings suggest that filters are not just fun toolsâthey actively shape perceptions of gender, self-worth, and digital identity.
Azuma, R. T. (1997). A survey of augmented reality. Presence: Teleoperators and Virtual Environments, 6(4), 355â385.
Burnell, K., Kurup, A. R., & Underwood, M. K. (2021). Snapchat lenses and body image concerns. Body Image, 38, 12â19.
Fredrickson, B. L., & Roberts, T. A. (1997). Objectification theory: Toward understanding womenâs lived experiences and mental health risks. Psychology of Women Quarterly, 21(2), 173â206.
Lawrence, S., & Cambre, C. (2020). âDo I look like my selfie?â: Filters and the digital-forensic gaze. Social Media + Society, 6(1), 1â13.
Miller, L., & McIntyre, M. (2022). From surgery to cyborgs: A thematic analysis of popular media commentary on Instagram filters. New Media & Society, 24(1), 123â140.
Perloff, R. M. (2014). Social media effects on young womenâs body image concerns: Theoretical perspectives and an agenda for research. Sex Roles, 71(11â12), 363â377.
Pescott, C. (2020). Children and digital filters: Understanding gendered technology use. Journal of Digital Culture, 7(2), 89â104.
Rajanala, S., Maymone, M. B. C., & Vashi, N. A. (2018). Selfiesâliving in the era of filtered photographs. JAMA Facial Plastic Surgery, 20(6), 443â444.
Rettberg, J. W. (2014). Seeing ourselves through technology: How we use selfies, blogs and wearable devices to see and shape ourselves. Palgrave Macmillan.
Peng, H. (2020). AI-powered beauty filters in digital banking: The case of AliPay. Journal of Digital Finance, 5(3), 215â229.