Automating beauty: Detecting facial changes in platform beauty filters

Beauty filters have become everyday instruments in digital media’s visual and participatory cultures. Such filters use AR (augmented reality) and AI (artificial intelligence) technologies and apply a digital mask over a user’s face and automate ‘corrections’ to a user’s face, most commonly skin smoothing, balancing features such as noses and eyes, and enhancing lips, in accordance with dominant racialised beauty expectations. In this article, we provide an overview of the evolution of AR and AI automation processes that are embedded in contemporary filters used in TikTok and Instagram and explore how filters and beauty expectations are experienced and navigated by young people. We found young people are highly suspicious of the automated changes filters can make to their faces ‘without asking’, and felt platforms should ‘own up’ to precisely how their faces are being changed. They were also critical of how filters repeat and reinforce existing gendered and racialised beauty norms, but found these norms harder to challenge when a supposedly ‘objective’ measure of beauty was reinscribed through the technology: ‘the filter tells you what your flaws are’. We situate these technologies as enabling the automation of ‘beauty’ and examine its impacts for prevailing gendered and racialised beauty norms and inequalities.