The Most FACE Ever builds intuition for how neural networks are used for face analysis by inviting users to play a game where they undertake challenges to trick an algorithm into mis-analyzing their face. The experience starts by detecting mundane attributes like SUNGLASSES or SMILE, but becomes increasingly problematic: detecting race, criminality, sexual orientation. Based on real machine learning research, it builds intuition for algorithms running the world. Typically computer vision happens slowly, it happens behind the scenes. An image captured by surveillance cameras, uploaded to Facebook, or scraped by a web crawler: they are ingested by the machines of corporations and governments, and analyzed out of sight. We never have an opportunity to inspect or interrogate these systems. The goal of The Most FACE Ever is to give people an opportunity to play with these dangerous tools in realtime, to playfully grow an intuition for what it means to see like a machine, and to understand how machines can fail.

Kyle McDonald is an artist working with code. 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. Working with machine learning, computer vision, social and surveillance tech spanning commercial and arts spaces.