Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/308012 
Year of Publication: 
2024
Citation: 
[Journal:] Democratization [ISSN:] 1743-890X [Volume:] 31 [Issue:] 5 [Publisher:] Taylor & Francis [Place:] London [Year:] 2024 [Pages:] 943-962
Publisher: 
Taylor & Francis, London
Abstract: 
While artificial intelligence technologies are increasingly studied as drivers of “digital authoritarianism,” resistance to this process has remained underexplored. Our paper addresses this gap by asking why and how citizens resist AI-powered autocratization in consolidated democracies. We first conceptualize this resistance as distinct from other forms of anti-autocratic resistance in that it is anticipatory rather than reactive, and directed at existing authorities rather than new democratic challengers. We then introduce techno-authoritarian imaginaries as a novel concept to understand the drivers and shapes of this resistance. First, we argue that activists from civil society draw on these broader, pre-existing imaginaries of authoritarian futures to make sense of new technologies and articulate technology-specific problem frames. Second, we propose that imaginaries are contingent on historical and political experiences and therefore differ between contexts. Such differences, in turn, shape how the respective targets respond to resistance. We illustrate our argument by case studies of campaigns against facial recognition technology in the U.S. and the European Union. Our paper enriches existing debates on resistance to autocratization and advocates or a more pronounced engagement with practices of future-making, as constructions of societal futures—both desirable and undesirable—are becoming an increasingly important source for democratic mobilization.
Subjects: 
Artificial intelligence
autocratization
facial recognition technology
surveillance
frames
sociotechnical imaginaries
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

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