User-Centered Machine Learning credit:

4 Hours

Introduces guidelines, processes, and systems for designing effective user experiences powered by machine learning models. Topics include design tradeoffs unique to data-driven products and services such as automation versus control, precision versus recall, and personalization versus privacy. Readings from human computer-interaction, product design, cognitive science, machine learning, computer vision, and natural language processing frame in-class design exercises. Students work in teams on a multi-week research project creating or auditing data-driven experiences. Prerequisite: CS 465 or equivalent course work.