Care and the Practice of Data Science for Social Good

Abstract

Data science is an interdisciplinary field that extracts insights from data through a multi-stage process of data collection, analysis and use. When data science is applied for social good, a variety of stakeholders are introduced to the process with an intention to inform policies or programs to improve well-being. Our goal in this paper is to propose an orientation to care in the practice of data science for social good. When applied to data science, a logic of care can improve the data science process and reveal outcomes of "good" throughout. Consideration of care in practice has its origins in Science and Technology Studies (STS) and has recently been applied by Human Computer Interaction (HCI) researchers to understand technology repair and use in under-served environments as well as care in remote health monitoring. We bring care to the practice of data science through a detailed examination of our engaged research with a community group that uses data as a strategy to advocate for permanently affordable housing. We identify opportunities and experiences of care throughout the stages of the data science process. We bring greater detail to the notion of human-centered systems for data science and begin to describe what these look like.