Mirror, Mirror on the Wall, Who Is the Whitest of All? Racial Biases in Social Media Beauty Filters

Abstract

Digital beauty filters are pervasive in social media platforms. Despite their popularity and relevance in the selfies culture, there is little research on their characteristics and potential biases. In this article, we study the existence of racial biases on the set of aesthetic canons embedded in social media beauty filters, which we refer to as the Beautyverse. First, we provide a historic contextualization of racial biases in beauty practices, followed by an extensive empirical study of racial biases in beauty filters through state-of-the-art face processing algorithms. We show that beauty filters embed Eurocentric or white canons of beauty, not only by brightening the skin color, but also by modifying facial features.

What is Beautiful is Still Good: The Attractiveness Halo Effect in the era of Beauty Filters

“…These filters offer a unique opportunity to study the attractiveness halo effect at scale, with diversity in the age, gender and ethnicity of the stimuli, and in a controlled scenario, because they allow the creation of beautified versions of the same individuals. Beauty filters however have been shown to profoundly impact user self-presentation, raising questions about authenticity, self-esteem [34], mental health [35], diversity [36] and racism [37]. Thus, there is a need to study the effect of these augmented appearances on how users are perceived and judged within digital environments, both by humans and by AI algorithms.…”