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2024 | OriginalPaper | Buchkapitel

Machine learning, political participation and the transformations of democratic self-determination

verfasst von : Jeanette Hofmann, Clara Iglesias Keller

Erschienen in: Künstliche Intelligenz, Mensch und Gesellschaft

Verlag: Springer Fachmedien Wiesbaden

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Abstract

This contribution addresses links between machine learning technologies and democracy with a focus on political participation. Democracy research often regards machine learning technologies as a threat, as these technologies could violate fundamental rights or replace democratic decision making. While raising important concerns, these approaches underestimate the malleability of digital technologies and their relationship to democracy. Our argument is that inherent to democratic practice we find a constant (re)negotiation of rights and institutions, in this case not least driven by the fact that machine learning technologies themselves are far from reaching maturity. The openness and negotiability of the relationship of AI and democracy is illustrated by three critical perspectives that hold special importance for political participation: algorithmic bias, automated decision-making and AI’s epistemic dimension. By reflecting the changing condition of political organisation, current research can be productive and even performative in the sense of co-defining a shared understanding of new technologies and aim to set standards for their legitimate use.

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Titel: Machine learning, political participation and the transformations of democratic self-determination
verfasst von: Jeanette Hofmann
Clara Iglesias Keller
Verlag: Springer Fachmedien Wiesbaden
Buch: Künstliche Intelligenz, Mensch und Gesellschaft
Print ISBN: 978-3-658-43520-2

Electronic ISBN: 978-3-658-43521-9

Copyright-Jahr: 2024
DOI: https://doi.org/10.1007/978-3-658-43521-9_13

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