Open face
For two years, I researched and tested emotion recognition technologies—sometimes with the intention of challenging them, other times with the desire to work alongside them. What began in deep skepticism gradually evolved into an attempt to understand how these systems operate: how they identify our emotions, and how they make decisions based solely on our faces muscles. Out of this encounter emerged a series of works that both question the limitations of the technology and explore how it might be used to expand the boundaries of language and emotional experience.
From this process grew the project “Open Faces”, which offers a critical alternative to existing technologies. Most of these rely on Paul Ekman’s theory, which claims the existence of six universal emotions identifiable through micro-facial expressions. This approach, which has become the foundation of a $20-billion industry, ignores the cultural and contextual complexity of emotions and narrows the space in which we come to understand ourselves.
״Sleeping Beauty" is a conceptual work that confronts the fundamental premise of emotion recognition technology. The project takes historical post-mortem photographs and submits them to an emotion recognition system. By presenting the technology with images of the deceased, the work creates an intentional paradox, forcing the system to perform a task it is inherently incapable of. This process not only exposes the absurd limitations of data-driven emotional analysis but also challenges the very notion that emotion can be reduced to quantifiable, surface-level expressions. The resulting misreadings, often bizarre and unsettling, generate poignant narratives that bridge the stillness of death with the technology’s frantic search for a fleeting emotional state. In doing so, "Sleeping Beauty" subverts the technology's claim to objectivity and provokes a deeper inquiry into the nature of emotion itself.
“Open face” grounded in Jacques Lacan’s theory of the symbolic stage—the idea that language shapes the very categories of our perception. Within this framework, Open Faces constructs a living, dynamic archive of facial expressions that expands with each new participant. This archive is not merely a collection of data, but a tool that generates entirely new emotions through collages of diverse faces—across cultures, genders, and ages. In doing so, it produces emotional categories absent from conventional language, while at the same time exposing a deeper limitation of the technology: its fixation on external “action units,” without engaging with the inner essence of the emotions that drive muscular movement.