During the Rapid Response fellowship, McDonald researched the intersection of face analysis and policing.
American police have been running face recognition on surveillance cameras for nearly 20 years. While there have been many investigations into face detection and recognition, today advances in machine learning are weaponized to estimate everything from age and facial expressions to race and gender. This analysis happens behind the scenes on billboards, social media, and policing systems, often trained on publicly accessible data. A deeper understanding of this tech will give us the tools we need to dismantle it — whether in public spaces monitored by surveillance cameras, or personal webcams and mobile cameras monitored by big tech companies.
Kyle McDonald is an artist working with code based in Los Angeles. He crafts interactive installations, sneaky interventions, playful websites, workshops, and toolkits for other artists working with code. Exploring possibilities of new technologies: to understand how they affect society, to misuse them, and build alternative futures; aiming to share a laugh, spark curiosity, create confusion, and share spaces with magical vibes. McDonald works with machine learning, computer vision, social and surveillance tech spanning commercial and arts spaces. Previously adjunct professor at NYU’s ITP, member of F.A.T. Lab, community manager for openFrameworks, and artist in residence at STUDIO for Creative Inquiry at CMU, and YCAM in Japan. Work commissioned and shown around the world, by: the V&A, NTT ICC, Ars Electronica, Sonar, Today’s Art, and Eyebeam.