Human-Centered Machine Learning

This collection of articles and interviews surveys human-centered approaches to machine learning that can make AI more human-friendly, usable, and ethical. It provides a handbook for students, researchers, and practitioners who want new ways of approaching AI that place humanity at their center. It shows how to apply methods from human-computer interaction to the new technologies of AI and ML with a view to enabling computing technology to become user-friendly and human-centric. The book has 13 articles and 9 interviews from a range of different perspectives, helping readers understand existing machine learning systems and their impacts on people and society. It is an ideal introduction both for human-computer interaction practitioners who are interested in working with ML and for ML experts interested in making their practice more human-centered. The book offers a critical lens on existing machine learning alongside an optimistic vision of AI in the service of humanity.

Rebecca Fiebrink is Professor of Creative Computing at the University of the Arts London Creative Computing Institute. She works on new technologies to enable new forms of human expression, creativity, and embodied interaction. She developed the Wekinator tool for real-time interactive machine learning, which enables creative practitioners to develop new real-time, gestural interactions.

Marco Gillies is Professor of Computing at Goldsmiths, University of London and has a Ph.D. from the University of Cambridge. He has more than twenty-five years of experience working at the interface of artificial intelligence and virtual reality, in particular, using human-centered machine learning to develop new, embodied ways of interacting with VR.

Gonzalo Ramos is Principal Researcher at Microsoft Research in Redmond. He currently works on ideating, developing, and studying ways in which technology can both protect and augment people's cognition. As Researcher and Creative Technologist, he has helped develop frameworks such as Interactive Machine Teaching as well as novel experiences with direct interaction with videos, 3D scenes, and remote environments.