TY - GEN
T1 - Epistemic Injustice and Government Information Systems
T2 - Lessons from Two Cases
AU - Hulstijn, Joris
AU - Dong, Huimon
AU - Markovich, Réka
N1 - Publisher Copyright:
© IFIP International Federation for Information Processing 2024.
PY - 2024/8/21
Y1 - 2024/8/21
N2 - 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.
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.
UR - http://www.scopus.com/inward/record.url?scp=85202620597&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-70274-7_26
DO - 10.1007/978-3-031-70274-7_26
M3 - Conference contribution
SN - 978-3-031-70273-0
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 419
EP - 437
BT - Electronic Government - 23rd IFIP WG 8.5 International Conference, EGOV 2024, Proceedings
A2 - Janssen, Marijn
A2 - Crompvoets, Joep
A2 - Gil-Garcia, J. Ramon
A2 - Lee, Habin
A2 - Lindgren, Ida
A2 - Nikiforova, Anastasija
A2 - Viale Pereira, Gabriela
PB - Springer
ER -