In a world where digital systems are constantly categorising and labelling us, Beyond Binary looks at what happens when facial recognition technology meets non-binary and queer identity. The central question driving the project is pretty straightforward: how do algorithms — especially the ones used by big tech platforms — actually interpret and read queerness? Developed in collaboration with Giulia Carla Rossi, the project takes inspiration from artists like Arca, Linn da Quebrada, Raya, and Cássils, who are all actively pushing against rigid gender norms and testing the limits of what digital platforms will and won't allow. Their work sits in this interesting tension between visibility and invisibility — existing online in ways that constantly challenge how algorithms are designed to see people. From there, Beyond Binary went experimental: we built a database of portraits that blend male and female features using machine learning, aiming to reflect some of the real diversity within the LGBTQ+ community. Those portraits were then posted on Instagram and run through an open-source facial recognition library to see how they'd be gendered — and what that reveals about the assumptions baked into these systems.