Epistemic Injustice and Government Information Systems: Lessons from Two Cases

Joris Hulstijn; Huimon Dong; Réka Markovich

doi:10.1007/978-3-031-70274-7_26

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 proceeding › Conference contribution › Academic › peer-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 language	English
Title of host publication	Electronic Government - 23rd IFIP WG 8.5 International Conference, EGOV 2024, Proceedings
Editors	Marijn Janssen, Joep Crompvoets, J. Ramon Gil-Garcia, Habin Lee, Ida Lindgren, Anastasija Nikiforova, Gabriela Viale Pereira
Publisher	Springer
Chapter	26
Pages	419-437
Number of pages	19
ISBN (Electronic)	978-3-031-70274-7
ISBN (Print)	978-3-031-70273-0
DOIs	https://doi.org/10.1007/978-3-031-70274-7_26
Publication status	Published - 21 Aug 2024

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	14841 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Bibliographical note

Publisher Copyright:
© IFIP International Federation for Information Processing 2024.

Funding

This work is supported by the Fonds National de la Recherche of Luxembourg through the project Deontic Logic for Epistemic Rights (OPEN O20/14776480), and the project Deep Data Science of Digital History (D4H).

Funders	Funder number
Fonds National de la Recherche Luxembourg	O20/14776480

Access to Document

10.1007/978-3-031-70274-7_26

978-3-031-70274-7_26Final published version, 355 KBLicence: Taverne

Cite this

Hulstijn, J., Dong, H., & Markovich, R. (2024). Epistemic Injustice and Government Information Systems: Lessons from Two Cases. In M. Janssen, J. Crompvoets, J. R. Gil-Garcia, H. Lee, I. Lindgren, A. Nikiforova, & G. Viale Pereira (Eds.), Electronic Government - 23rd IFIP WG 8.5 International Conference, EGOV 2024, Proceedings (pp. 419-437). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14841 LNCS). Springer. https://doi.org/10.1007/978-3-031-70274-7_26

Hulstijn, Joris ; Dong, Huimon ; Markovich, Réka. / Epistemic Injustice and Government Information Systems : Lessons from Two Cases. Electronic Government - 23rd IFIP WG 8.5 International Conference, EGOV 2024, Proceedings. editor / Marijn Janssen ; Joep Crompvoets ; J. Ramon Gil-Garcia ; Habin Lee ; Ida Lindgren ; Anastasija Nikiforova ; Gabriela Viale Pereira. Springer, 2024. pp. 419-437 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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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.",

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Hulstijn, J, Dong, H & Markovich, R 2024, Epistemic Injustice and Government Information Systems: Lessons from Two Cases. in M Janssen, J Crompvoets, JR Gil-Garcia, H Lee, I Lindgren, A Nikiforova & G Viale Pereira (eds), Electronic Government - 23rd IFIP WG 8.5 International Conference, EGOV 2024, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 14841 LNCS, Springer, pp. 419-437. https://doi.org/10.1007/978-3-031-70274-7_26

Epistemic Injustice and Government Information Systems: Lessons from Two Cases. / Hulstijn, Joris; Dong, Huimon; Markovich, Réka.
Electronic Government - 23rd IFIP WG 8.5 International Conference, EGOV 2024, Proceedings. ed. / Marijn Janssen; Joep Crompvoets; J. Ramon Gil-Garcia; Habin Lee; Ida Lindgren; Anastasija Nikiforova; Gabriela Viale Pereira. Springer, 2024. p. 419-437 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14841 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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PY - 2024/8/21

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AB - 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.

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Hulstijn J, Dong H, Markovich R. Epistemic Injustice and Government Information Systems: Lessons from Two Cases. In Janssen M, Crompvoets J, Gil-Garcia JR, Lee H, Lindgren I, Nikiforova A, Viale Pereira G, editors, Electronic Government - 23rd IFIP WG 8.5 International Conference, EGOV 2024, Proceedings. Springer. 2024. p. 419-437. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-70274-7_26