Epistemic Injustice and Government Information Systems: Lessons from Two Cases

Joris Hulstijn*, Huimon Dong, Réka Markovich

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

Cases of bias and unfair decisions in automated decision-making are heavily discussed. When unfair decisions can be attributed to a difference in the knowledge of groups of subjects, we can speak of epistemic injustice (Fricker). In this paper, we analyse the various types of epistemic injustice: testimonial, hermeneutical, distributional, and content-focused epistemic injustice, and show how they can be conceptualised. We apply the notion of epistemic injustice to analyse what went wrong in two automated decision making scandals: Toeslagenaffaire (Netherlands), and RoboDebt (Australia). We discuss key observations from the cases and show that they can be categorised as various types of epistemic injustice. Based on these observations, we draw lessons about governance of automated decision making systems.
Original languageEnglish
Title of host publicationElectronic Government - 23rd IFIP WG 8.5 International Conference, EGOV 2024, Proceedings
EditorsMarijn Janssen, Joep Crompvoets, J. Ramon Gil-Garcia, Habin Lee, Ida Lindgren, Anastasija Nikiforova, Gabriela Viale Pereira
PublisherSpringer
Chapter26
Pages419-437
Number of pages19
ISBN (Electronic)978-3-031-70274-7
ISBN (Print)978-3-031-70273-0
DOIs
Publication statusPublished - 21 Aug 2024

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14841 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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