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Machine Learning, Political Participation and the Transformations of Democratic Self-Determination

Author: Hofmann, J., Iglesias Keller, C.
Published in: M. Heinlein, N. Huchler (Eds.), Künstliche Intelligenz, Mensch und Gesellschaft. Soziale Dynamiken und gesellschaftliche Folgen einer technologischen Innovation (pp. 321-344). Wiesbaden, Germany: Springer VS.
Year: 2024
Type: Book contributions and chapters
DOI: 10.1007/978-3-658-43521-9_13

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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