Human-Centered Machine Learning

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.

• 1. Introduction Rebecca Fiebrink, Marco Gillies and Gonzalo Ramos; Part I. Human-Centered Machine Learning in the Arts and Humanities: 2. Interviews: people Rebecca Fiebrink, Marco Gillies and Gonzalo Ramos; 3. Humanities and human-centered machine learning David Mimno and Laure Thompson; 4. Machine learning in movement-based interaction for performing arts applications Frederic Bevilacqua, Jules Françoise, Sarah Fdili Alaoui and Baptiste Caramiaux; Part II. Doing Human-Centered Machine Learning: 5. Measuring the user experience of human-centered machine learning: trust, intelligibility, and more Simone Stumpf and Alison Smith-Renner; 6. Data for machine learning: a human-centered perspective of crowdsourcing Edith Law and Ming Yin; 7. REDesigning AI products and services: benefits, challenges, and ideas for improving design practice Jodi Forlizzi, John Zimmerman, Qian Yang, Changhoon Oh and Nur Yildirim; Part III. Humans and Machine Learning: 8. Human-centered explainable AI (XAI): from algorithms to user experiences Q Vera Liao and Kush R. Varshney; 9. Humans teaching machine learning agents Samantha Krening; 10. Modeling the social and normative context of human-agent interactions Marynel Vìazquez, Hatice Gunes, Tom Williams and Ryan Blake Jackson; 11. Interviews: teams Rebecca Fiebrink, Marco Gillies and Gonzalo Ramos; Part IV. Machine Learning in Its Social Context: 12. A use-appraise-modify-create learning progression (UAMC) and a machine learning education framework (MLEF) for the development of AI-engaged citizens Natalie Lao and Irene Lee; 13. Artificially intelligent technology for the margins: reflecting on challenges and opportunities Tanja Aal, Jasmin Niess, Konstantin Aal, Douglas Zytko, Soaad Hossain, Giovanna Nunes Vilaza, Reem Talhouk, Heloisa Caroline de Souza Pereira Candello, Evangelos Kapros, Maria Koutsombogera, Franziska Tachtler, Daniel Diethei, Mohammed Khwaja, Shaimaa Lazem, Aneesha Singh, Marguerite Barry, Geraldine Fitzpatric, Volker Wulf and Claudia Müller; 14. The anatomy of the saliency cropping leviathan Vinay Uday Prabhu and Abeba Birhane; Part V. Machine Learning and Humanity: 15. Interviews: humanity Rebecca Fiebrink, Marco Gillies and Gonzalo Ramos; 16. Conclusion Rebecca Fiebrink, Marco Gillies and Gonzalo Ramos.