Journal
COMMUNICATION MONOGRAPHS
Volume 85, Issue 1, Pages 57-80Publisher
ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
DOI: 10.1080/03637751.2017.1375130
Keywords
Methodology; Big Data; AI; machine learning; epistemology; ethnography
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Funding
- Direct For Computer & Info Scie & Enginr
- Div Of Information & Intelligent Systems [1633400] Funding Source: National Science Foundation
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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.
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