Emerging Perspectives in Human-Centered Machine Learning

Abstract

Current Machine Learning (ML) models can make predictions that are as good as or better than those made by people. The rapid adoption of this technology puts it at the forefront of systems that impact the lives of many, yet the consequences of this adoption are not fully understood. Therefore, work at the intersection of people's needs and ML systems is more relevant than ever. This area of work, dubbed Human-Centered Machine Learning (HCML), re-thinks ML research and systems in terms of human goals. HCML gathers an interdisciplinary group of HCI and ML practitioners, each bringing their unique, yet related perspectives. This one-day workshop is a successor of Gillies et al. 2016 CHI Workshop and focuses on recent advancements and emerging areas in HCML. We aim to discuss different perspectives on these areas and articulate a coordinated research agenda for the XXI century.