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When AI says who made it: A meta-analysis of AI disclosure effects on consumer responses

Truvace record
TRV-2026-2705raw data (JSON)
Version
v1Published
First published
Evidence type
Systematic review or meta-analysis
Sources
1 sourcePeer-reviewed
sha256
4c7365a02adc…check it

Artificial intelligence (AI) is increasingly embedded in digital communications, yet the behavioral consequences of disclosing AI authorship remain inconsistent across studies. This meta-analysis synthesizes 21 experimental effect sizes (N = 13,582) to estimate the effect of AI disclosure on human behavioral responses—trust, attitudes, and behavioral intentions—and to identify the conditions under which it is strongest. Using a DerSimonian–Laird random-effects model, the pooled effect is significant and negative…

The problem

A meta-analysis of 21 experiments with 13,582 participants found that disclosing AI authorship reduced trust, attitudes and behavioral intentions (Hedges' g = −0.440), with every experiment pointing the same way.

What this doesn’t fix

Results varied substantially across the pooled studies (I² = 80.5%), and the apparent link between sample size and effect size was confounded with task context, so the moderator findings rest on a small set of 21 effect sizes.

Sources

1 on file
  1. Computers in Human Behavior Reportsdoi:10.1016/j.chbr.2026.101345
    Peer-reviewed2026-09-23

What the review found when it combined the studies

These are the review’s own pooled results, copied from its abstract. Truvace did not recalculate them.

  • Human trust, attitudes and behavioral intentions when AI authorship is disclosed versus not disclosed

    Hedges' g −0.440 (95% CI −0.532 to −0.348)

    21 studies · 13,582 people

    The review’s own words
    the pooled effect is significant and negative (Hedges' g = −0.440, 95% CI [−0.532, −0.348])

Code checks every number above against the review’s text before it is shown. The short labels are an AI model’s reading of that text, so the review’s own sentence sits under each one. A pooled figure is only as strong as the studies behind it. How Truvace uses pooled results

Cite this record

v1

Truvace Impact Record TRV-2026-2705, v1: “When AI says who made it: A meta-analysis of AI disclosure effects on consumer responses.” Truvace, 2026-11-12. /record/TRV-2026-2705 (accessed on the day you copy it). sha256 4c7365a02adc2a3d…

Change history

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  1. Publishedv14c7365a02adc…

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