Human-centered Machine Learning: a Machine-in-the-loop Approach

Human performance is not always an upper bound for machine learning.

Automation is not always the goal of machine learning.

A machine-in-the-loop approach

Human-in-the-loop machine learning, e.g., interactively training a machine learning system in crayons by correcting machine outputs in each round; recommender systems similarly involve the loop between humans and machines in which machines keep improving by learning from user feedback.
Machine-in-the-loop where humans take full agency and machines play a supporting role, e.g., machines can provide suggestions to inspire creativity and help writers overcome cognitive inertia.



Assistant Professor @CUBoulder, postdoc @UW, PhD @Cornell, study NLP and social interaction, computational social science.

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