Data Science for Social Good Volunteer Motivations and Limitations: An Exploratory Survey

Abstract

Broadly understood as the Data for Good (D4G) movement, coordinated efforts between technologists, domain experts, and mission driven organizations are addressing some of the world’s most pressing challenges using data science and AI applications to. One prominent mode of D4G engagement is skills-based volunteering, such as the work conducted by DataKind, a global nonprofit that pairs pro bono technologists with social sector organizations. This article examines D4G volunteering, reporting on findings from DataKind’s global volunteer survey that explores the community’s characteristics, motivations, and even the limitations that hinder long-term project engagement. As a global data collection and assessment effort of a self-identified D4G community, this study informs the broader community of practice and collaboration opportunities, which seek to advance a more equitable and ethical D4G ecosystem.