The Crisis of Social Categories in the Age of AI

Jean-Marie John-Mathews; Dominique Cardon

doi:10.6092/issn.1971-8853/15931

Authors

Jean-Marie John-Mathews Sciences Po; Université Paris-Saclay https://orcid.org/0000-0001-8049-1222

Jean-Marie John-Mathews is a researcher in algorithmic ethics. He is the coordinator of the Good In tech academic chair (Institut Mines Télécom / Sciences Po) and teaches at Sciences Po, Université PSL and Université Paris-Dauphine.

His research focuses on the development of so-called “responsible” tools in artificial intelligence and has been published in several scientific journals such as Technological Forecasting and Social Change and Journal of Business Ethics as well as in international conferences such as the International Conference on Information Systems.
Dominique Cardon Sciences Po; Université Paris Est https://orcid.org/0000-0002-3892-9611

Dominique Cardon is Professor of Sociology at Sciences Po where he directs the Médialab.

His work focuses on the uses of the Internet and the transformations of the digital public space. His recent research focuses on Internet social networks, forms of online identity, amateur self-production, the analysis of forms of cooperation and governance in large online collectives, and the analysis of the algorithms used to organize information on the web.

He has notably published La démocratie Internet (Paris, Seuil/La République des idées, 2010), A quoi rêvent les algorithmes. Nos vies à l'heure des big data (Paris, Seuil/République des idées, 2015) and, with Jean-Philippe Heurtin, Chorégraphier la générosité. Le Téléthon, le don et la critique (Paris, Économica, 2016), Culture numérique (Paris, Presses de Sciences Po, 2019).

DOI:

https://doi.org/10.6092/issn.1971-8853/15931

Keywords:

AI, Machine learning, Social categories

Abstract

This article explores the change in calculation methods induced by deep learning techniques. While more traditional statical methods are based on well instituted categories to measure the social world, these categories are today denounced as a set of hardened and abstract conventions that are incapable of conveying the complexification of social life and the singularities of individuals. Today AI models try to overcome some criticism raised by rigid social categories by combining a "spatial and temporal expansion" of the data space, producing a global transformation of the calculation methods.

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The Crisis of Social Categories in the Age of AI

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