Between technochauvinism and human-centrism: Can algorithms improve decision-making in democratic politics?

Pascal D. König, Georg Wenzelburger

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

The promise of algorithmic decision-making (ADM) lies in its capacity to support or replace human decision-making based on a superior ability to solve specific cognitive tasks. Applications have found their way into various domains of decision-making—and even find appeal in the realm of politics. Against the backdrop of widespread dissatisfaction with politicians in established democracies, there are even calls for replacing politicians with machines. Our discipline has hitherto remained surprisingly silent on these issues. The present article argues that it is important to have a clear grasp of when and how ADM is compatible with political decision-making. While algorithms may help decision-makers in the evidence-based selection of policy instruments to achieve pre-defined goals, bringing ADM to the heart of politics, where the guiding goals are set, is dangerous. Democratic politics, we argue, involves a kind of learning that is incompatible with the learning and optimization performed by algorithmic systems.
Original languageEnglish
Pages (from-to)132-149
JournalEuropean Political Science
Volume21
Issue number1
DOIs
Publication statusPublished - Mar 2022

Funding

We would like to thank the anonymous reviewers for their constructive comments. The manuscript also owes to discussions with Anja Achtziger, Julia Felfeli, Adam Harkens, Tobias Krafft, Johannes Schmees, Wolfgang Schulz, Karen Yeung, and Katharina Zweig Acknowledgments We would like to thank the anonymous reviewers for their constructive comments. The manuscript also owes to discussions with Anja Achtziger, Julia Felfeli, Adam Harkens, Tobias Krafft, Johannes Schmees, Wolfgang Schulz, Karen Yeung, and Katharina Zweig Funding Open Access funding enabled and organized by Projekt DEAL. The authors disclose receipt of the following financial support for the research, authorship, and/or publication of this article: This research has been conducted within the project “Deciding about, by, and together with algorithmic decision-making systems,” funded by the Volkswagen foundation.

FundersFunder number
Katharina Zweig
Volkswagen Foundation

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