Providing explanations widens the human–AI gap in perceived fairness, with a larger fairness improvement in the teacher condition¶
Claim · All claims
Evidence · 1 study · causalr2·q3
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person
Subclaims¶
Reading the evidence codes
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q3 i? Simple-effect analysis showed scoring explanations raised perceived fairness under both agent conditions, with a larger improvement in the teacher group. → Zhang Zhen; Fan Siyu; Qi Chunhui 2026
Evidence¶
Zhang Zhen; Fan Siyu; Qi Chunhui 2026¶
Zhang Zhen; Fan Siyu; Qi Chunhui. (2026). Teacher or Artificial Intelligence? The Effect of Decision-Making Agent on Junior High School Students’ Decision Acceptance: A Moderated Mediation Model. Behavioral Sciences. https://doi.org/10.3390/bs16071227
q3 · i? · causal · r2
Follow-up simple-effect analyses after the significant two-way interaction on perceived fairness (F(1,246) = 5.99, p = 0.015, partial η2 = 0.02) showed explanations raised fairness in both conditions, with the teacher group rising from 3.17 to 3.99 and the AI group from 2.86 to 3.11.
"A follow-up simple-effect analyses indicated that, for both decision-maker conditions, perceived fairness was significantly greater when grading explanations were available: Teacher condition: with explanation (M = 3.99, SD = 0.79) > without explanation (M = 3.17, SD = 1.03); AI condition: with explanation (M = 3.11, SD = 0.92) > without explanation (M = 2.86, SD = 0.92)."
Discussion¶
Related Claims¶
- Explanatory feedback alone raises both perceived fairness and decision acceptance, and the indirect effect of agent on acceptance is significant only when explanations are provided — related
- Explanatory feedback positively moderates only the path from decision-making agent to perceived fairness, not the direct path to decision acceptance — a broader claim this one bears on
- Perceived fairness partially mediates the effect of decision-making agent on decision acceptance, accounting for 67.52% of the total effect — related
- Junior high school students report significantly higher acceptance of teacher-made grading decisions than AI-generated decisions — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
explanations-widen-fairness-gap |
title |
Providing explanations widens the human–AI gap in perceived fairness, with a larger fairness improvement in the teacher condition |
description |
Providing explanations widens the human–AI gap in perceived fairness, with a larger fairness improvement in the teacher condition |
status |
review |
evidence_strength |
moderate |
newest_evidence |
2026 |
generated |
by process:wiki-ingest on 2026-10-12 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — zhang-zhen-fan-siyu-qi-chunhui-2026 |
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