DESCRIPTION
The Algorithmic Society Chair at MIAI takes on a threefold challenge to understand the algorithmic shift in society: an
empirical a challenge that involves studying AI within its immediate social contexts, an experimental challenge that proposes innovative interdisciplinary research on biases and other forms of social influence in AI, and a
cultural challenge by promoting a new understanding of AI among social science students.
ACTIVITIES
The Chair focuses particularly on the impact of the algorithmic turn on social worlds previously governed by institutional and organizational rules (such as the labor market and the public sphere) or by professional knowledge (such as hospitals, courts, newsrooms, or city planning offices). It promotes fieldwork research based on well-established social science methods (interviews, observation, text mining, and career analysis) and experiments.
The Chair conducts research on the social contexts and conditions of AI deployment in various social settings where AI interacts with professional knowledge and organizational constraints—such as medical treatment in hospitals, judicial decision-making in courts, urban planning, and media activity. It also studies public perception of AI, a topic that remains a blind spot in France. To this end, large-scale text mining research based on the analysis of legacy and social media corpora is conducted. The Chair also focuses on studying those who contribute to the development of these algorithms, their career paths, backgrounds, skills, and perceptions of society.
In addition, the Chair has established an Open AI Lab to foster research based on collaboration between social scientists and computer scientists, with the aim of contributing to a better understanding of how algorithms work and a critical assessment of the effects of AI on society. In collaboration with partners such as AFP, a specific focus is placed on the creation of biases and the reduction of viewpoint diversity in the public sphere resulting from the spread of news and comments via algorithms.
CHAIR EVENTS
The Chair holds a regular seminar on Friday afternoons.
The program is available at
https://algorithmicsociety.github.io/seminaire.html
TEAM MEMBERS
Isabelle Allegret (UGA / Citizen Campus). Isabelle Allegret directs the Citizen Campus program, which trains students in public debate on major issues at the intersection of science and society
https://citizencampus.univ-grenoble-alpes.fr/. Contact:
isabelle.allegret@univ-grenoble-alpes.fr.
Gilles Bastin (Sciences Po Grenoble / Pacte). Gilles Bastin is a professor of sociology. He coordinates the activities of the “ chair ” and is involved in several projects on the algorithmization of the media and research on algorithmic biases related to gender and social class in the distribution of information. He teaches the course “Algorithmic Society” at Sciences Po Grenoble.
More info. Contact:
gilles.bastin@iepg.fr.
Marine Bourgeois (Sciences Po Grenoble / Pacte). Marine Bourgeois is an associate professor of political science. Her research focuses on the use of ranking algorithms in housing policy in France.
More info. Contact:
marine.bourgeois@iepg.fr.
Sylvain Bouveret (Grenoble INP-UGA / LIG). Sylvain Bouveret is an associate professor of computer science. His research focuses on computational social choice and resource allocation algorithms.
More info. Contact:
sylvain.bouveret@imag.fr.
Vincent Bullich (Grenoble Alpes University / Gresec). Vincent Bullich is an associate professor of information and communication sciences. His research focuses on recommendation algorithms and digital regimes of visibility for cultural content.
More info. Contact:
vincent.bullich@univ-grenoble-alpes.fr.
Nicolas Douay (Grenoble Alpes University / Pacte). Nicolas Douay is a professor of urban planning. He researches the use of artificial intelligence in urban planning.
More info. Contact:
nicolas.douay@univ-grenoble-alpes.fr.
Laurence Dumoulin (CNRS / Pacte), Laurence Dumoulin is a research fellow at the CNRS. She studies innovation in the justice system and French initiatives in the field of predictive justice.
More info. Contact:
laurence.dumoulin@umrpacte.fr.
Jean Finez (Grenoble Alpes University / Pacte). Jean Finez is an associate professor of sociology. His research focuses on online exchange platforms, particularly webcamming and the social trajectories of camgirls.
More info. Contact:
jean.finez@univ-grenoble-alpes.fr.
Paolo Frasca (CNRS / GIPSA). Paolo Frasca is a research fellow at the CNRS. He works on the mathematical formalization of the effects of online recommendation systems.
More info. Contact:
paolo.frasca@gipsa-lab.grenoble-inp.fr.
Severine Louvel (Sciences Po Grenoble / Pacte). Séverine Louvel is an associate professor of sociology. Her research focuses on the use of artificial intelligence in patient care in hospitals.
More info. Contact:
severine.louvel@iepg.fr.
Emmanuel Marty (UGA / Gresec). Emmanuel Marty is an associate professor of information and communication sciences. He researches media coverage of artificial intelligence in France (with Nathalie Walcsak) and cultural recommendation systems (with Vincent Bullich).
More info. Contact:
emmanuel.marty@univ-grenoble-alpes.fr.
Kavé Salamatian (USMB / LIPSTIC). Kavé Salamatian is a professor of computer science. His research focuses on the Internet of the future, distributed signal processing, network metrology, and cooperation theory.
More info. Contact:
kave.salamatian@univ-savoie.fr.
Nathalie Walczak (UGA / Gresec). Nathalie Walczak is an associate professor of information and communication sciences. She is researching the public debate on AI in France (with Emmanuel Marty).
More info. Contact:
nathalie.walczak@univ-grenoble-alpes.fr.
SELECTED LIST OF PUBLICATIONS
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Maria Castaldo, Tommaso Venturini, Paolo Frasca, Floriana Gargiulo. “Junk News Bubbles: Modelling the Rise and Fall of Attention in Online Arenas.” *New Media and Society*, SAGE Publications, in press, pp. 1–15. ⟨10.1177/1461444820978640⟩.
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Wilbert Rossi, Jan Polderman, Paolo Frasca. “The Closed Loop Between Opinion Formation and Personalized Recommendations.” *IEEE Transactions on Control of Network Systems*, IEEE, 2021, pp. 1–12. ⟨10.1109/TCNS.2021.3105616⟩.
