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The ethnographer and the algorithm

Angèle Christin will present this second session of the online seminar; she will present her recent work and explain the necessary links between algorithms and ethnographic research

Event, Research Seminar

This session is organized in partnership with the Centre Internet et Société (CIS).

Abstract

A common theme in the literature on algorithms is that they are profoundly opaque and function as “black boxes.” Scholars have suggested several methodological approaches in order to bypass algorithmic opacity. Here Angèle Christin argues that we need to explicitly enroll algorithms in ethnographic research, which can shed light on unexpected aspects of algorithmic systems – including their opacity. She delineates three meso-level strategies for algorithmic ethnography. The first, algorithmic refraction, examines the resonance and effects of computational software on the people and institutions who use them. The second strategy, algorithmic comparison, relies on a similarity-and-difference approach to identify the instruments' specific features. The third strategy, algorithmic triangulation, enrolls algorithms to help gather rich qualitative data and mediate one’s position in the field. Angèle Christin concludes by discussing the implications of this toolkit for the study of sociotechnical systems and future of ethnographic fieldwork.

Biography

Angèle Christin is an assistant professor in the Department of Communication and affiliated faculty in the Sociology Department and Program in Science, Technology, and Society at Stanford University. She studies how algorithms and analytics transform professional values, expertise, and work practices.

Practical information

This seminar will be broadcast online. Think about testing the system before the seminar.

Recommended Reading

A. Christin. 2018. “Counting Clicks. Quantification and Variation in Web Journalism in the United States and France.” American Journal of Sociology 123 (5): 1382-1415.

A. Christin. 2017. “Algorithms in Practice: Comparing Web Journalism and Criminal Justice.” Big Data & Society 4 (2): 1-14. 

S. Brayne, and A. Christin. 2020. “Technologies of Crime Prediction: The Reception of Algorithms in Policing and Criminal Courts” Social Problems Online First, 1-17.