Document Type
Article
Publication Date
7-20-2026
Journal / Book Title
Informatics
Abstract
This study investigates consumer perceptions of procedural and distributive fairness/unfairness in service interactions involving AI versus human providers. It also examines how these perceptions are influenced by technology-related discomfort and the perceived responsibility of the service organization. A scenario-based online experiment was conducted using participants recruited through the Prolific research platform. Participants were asked to review a small business loan application process at a fictional digital bank where the application is processed either by an AI algorithm or a human loan officer. The study found that consumers experienced a higher level of satisfaction when they encountered procedural unfairness from humans compared to AI. The negative effect of procedural unfairness on satisfaction was amplified as algorithm discomfort and perceived company responsibility increased. The findings suggest that AI unfairness requires special attention to address differences in consumer reaction.
DOI
10.3390/informatics13070116
MSU Digital Commons Citation
Johnson, Devon S.; Chun, Sungyong; Pandey, Sneha; and Ahmed, Gouher, "Procedural and Distributive Unfairness in AI Interactions: Are People Less Satisfied with Unfairness from AI Compared to Humans?" (2026). Department of Marketing Faculty Scholarship and Creative Works. 285.
https://digitalcommons.montclair.edu/marketing-facpubs/285
Rights
© 2026 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.
Published Citation
Johnson, D., Chun, S., Pandey, S., & Ahmed, G. (2026). Procedural and Distributive Unfairness in AI Interactions: Are People Less Satisfied with Unfairness from AI Compared to Humans? Informatics, 13(7), 116. https://doi.org/10.3390/informatics13070116