Situating methods in the magic of Big Data and AI

Item Type Journal Article Author M. C. Elish Author danah boyd URL https://doi.org/10.1080/03637751.2017.1375130 Volume 85 Issue 1 Pages 57-80 Publication Communication Monographs ISSN 0363-7751 Date 2018-01-02 Extra Publisher: Routledge _eprint: https://doi.org/10.1080/03637751.2017.1375130 DOI 10.1080/03637751.2017.1375130 Accessed 2024-08-13 13:50:18 Library Catalog Taylor and Francis+NEJM Abstract “Big Data” and “artificial intelligence” have captured the public imagination and are profoundly shaping social, economic, and political spheres. Through an interrogation of the histories, perceptions, and practices that shape these technologies, we problematize the myths that animate the supposed “magic” of these systems. In the face of an increasingly widespread blind faith in data-driven technologies, we argue for grounding machine learning-based practices and untethering them from hype and fear cycles. One path forward is to develop a rich methodological framework for addressing the strengths and weaknesses of doing data analysis. Through provocatively reimagining machine learning as computational ethnography, we invite practitioners to prioritize methodological reflection and recognize that all knowledge work is situated practice.