Ernest is an interactive exploration of machine learning, placing the viewer in the role of training an artificial intelligence designed to make people happy. It uses computer vision to detect the user, gauge, measure, and react to their emotions based on the user's facial expressions.

It serves to open a dialogue around the ethics of gathering the data used to train and validate models, the gap between intent and real-world applications of these models, and the tensions around applying automated decision making to imperfect or inaccurate models.

By demystifying and simplifying the mechanics of machine learning through an experiential installation, we will open the door to broader understanding and questioning of the underlying technology and its potential societal impact.

Ernest has been developed by Sean Mulholland with support from Matt Visco and IDEO San Francisco.