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COMP_SCI 396, 496: Human-Centered Machine Learning

Quarter Offered

Fall : 2:40-4 TuTh ; Chancellor

Prerequisites

Instructor permission

Description

Machine learning has stirred tremendous excitement in popular science, as it is being applied to problems of all shapes and sizes. This involves learning and predicting things that humans do naturally (see, hear, understand language), signals we give off unconsciously,  as well as decisions and ideas we have (make decisions, evaluate options, think creatively). These are captured under the broad banner of human-centered machine learning (HCML), an emergent research and practical area combining human interaction with machine learning and studying the impacts of systems in the world.

In this class, we will study what human-centered machine learning is, how this idea is built and applied in technical systems, and critiques of machine learning from other domains that question if ML can be human-centered. There will be a strong emphasis in this seminar on reading and discussing current research on HCML, from a technical, critical, and social perspectives. Later, we will put these principles into practice in applying what we have learned in a group project. This class is intended to be interdisciplinary, with students drawn from CS and STEM as well as social sciences who use ML for their research and are thinking through essential questions on the impacts of ML in society.

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COURSE COORDINATOR: Stevie Chancellor
COURSE INSTRUCTOR:
Prof. Chancellor