Lay Perceptions of Algorithmic Discrimination in the Context of Systemic Injustice
Authors: G Lima, N Grgić-Hlača, M Langer, Y Zou
Published: 2025
Publication: Proceedings of the 2025 CHI ..., 2025 - dl.acm.org
The study examines how contextualizing algorithms within systemic injustice impacts perceptions of algorithmic discrimination, finding disparate effects based on participant group identity and revealing unintended consequences of such contextualization.
Methods: 2x3 between-participants experiment using the hiring context as a case-study; examined the influence of systemic injustice information and algorithms' bias perpetuation on lay perceptions.
Key Findings: Impact of systemic injustice framing and explanation of algorithmic bias perpetuation on participants' views of algorithmic fairness and discrimination.
Limitations: The study notes potential heterogeneous effects based on participant backgrounds, with unintended consequences for disadvantaged and advantaged groups, and the null effect of explaining algorithms' learning from human biases.
Institution: University of Maryland, Max Planck Institute, Stanford University, Cornell University
Research Area: Algorithmic Fairness, Systemic Injustice, Social Perception of AI, Algorithmic Discrimination
Discipline: Computational Social Science
Sample Size: 716 participants
Citations: 2
DOI: 10.1145/3706598.3713536