Does the Source of a Warning Matter? Examining the Effectiveness of Veracity Warning Labels Across Warners

TL;DR

This study investigates how the source of warning labels influences trust and sharing of false information, finding AI warnings most effective especially among those with low trust in news sources.

Contribution

It provides empirical evidence on the differential impact of warning sources, highlighting AI's superior effectiveness in reducing trust and sharing intentions for false info.

Findings

AI warnings most effectively reduce trust in false info.

Warnings from social media users are less effective.

Effectiveness of warnings varies with prior trust in media.

Abstract

In this study, we conducted an online, between-subjects experiment (N = 2,049) to better understand the impact of warning label sources on information trust and sharing intentions. Across four warners (the social media platform, other social media users, Artificial Intelligence (AI), and fact checkers), we found that all significantly decreased trust in false information relative to control, but warnings from AI were modestly more effective. All warners significantly decreased the sharing intentions of false information, except warnings from other social media users. AI was again the most effective. These results were moderated by prior trust in media and the information itself. Most noteworthy, we found that warning labels from AI were significantly more effective than all other warning labels for participants who reported a low trust in news organizations, while warnings from AI were no more effective than any other warning label for participants who reported a high trust in news organizations.