Strict With Humans, Lenient With Machines? Differential Effects of Artificial Intelligence Versus Human Unfairness on Trust

ABSTRACT Existing research has produced mixed findings regarding how individuals respond to unfair decisions enacted by AI versus human decision‐makers. A key limitation of prior research is that studies rarely distinguish among different forms of unfairness and have largely focused on moral reactions. Drawing on expectancy violation theory and mind perception theory, we conducted six vignette‐based experiments ( N = 1299) to examine how trust responses differ when distributive, procedural, and interactional unfairness are enacted by AI versus humans. Results show that (1) under distributive unfairness, participants reported significantly lower cognitive trust toward AI than toward humans; (2) under procedural and interactional unfairness, participants reported significantly higher cognitive trust toward AI than toward humans; and (3) across all types of unfairness, humans consistently evoked lower affective trust than AI. Mediation analyses further indicate that perceived ability and perceived benevolence serve as key explanatory mechanisms for cognitive and affective trust, respectively.

Authors

Institutions

Publication Details

Journal
Journal of Applied Social Psychology
Published
2026-08-03
DOI
https://doi.org/10.1111/jasp.70080
Primary Topic
Psychology of Moral and Emotional Judgment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Strict With Humans, Lenient With Machines? Differential Effects of Artificial Intelligence Versus Human Unfairness on Trust

Xuefei Wang, Yuxin Liu, Jianwei Zhang, Yang Luo
Journal of Applied Social Psychology
Psychology of Moral and Emotional Judgment
article

Strict With Humans, Lenient With Machines? Differential Effects of Artificial Intelligence Versus Human Unfairness on Trust

Xuefei Wang, Yuxin Liu, Jianwei Zhang, Yang Luo
article en

Abstract

ABSTRACT Existing research has produced mixed findings regarding how individuals respond to unfair decisions enacted by AI versus human decision‐makers. A key limitation of prior research is that studies rarely distinguish among different forms of unfairness and have largely focused on moral reactions. Drawing on expectancy violation theory and mind perception theory, we conducted six vignette‐based experiments ( N = 1299) to examine how trust responses differ when distributive, procedural, and interactional unfairness are enacted by AI versus humans. Results show that (1) under distributive unfairness, participants reported significantly lower cognitive trust toward AI than toward humans; (2) under procedural and interactional unfairness, participants reported significantly higher cognitive trust toward AI than toward humans; and (3) across all types of unfairness, humans consistently evoked lower affective trust than AI. Mediation analyses further indicate that perceived ability and perceived benevolence serve as key explanatory mechanisms for cognitive and affective trust, respectively.

Journal of Applied Social Psychology
Beijing Institute of Education (CN), University of International Business and Economics (CN)
Peace, Justice and strong institutions
Openalex Percentile: Top 8%
Psychology of Moral and Emotional Judgment
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.