Automating Accuracy: Scalable Approaches to Correcting Disinformation With Artificial Intelligence on Social Media

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Abstract
This study investigates whether source expertise (expert vs. non-expert), use of artificial intelligence (AI; AI vs. non-AI), and the placement (debunking vs. prebunking) of a correction influence its effectiveness in reducing misperceptions and intentions to consume raw milk. Results of a pre-registered two-wave online experiment ( N 1 = 1,785, N 2 = 1,568) suggest that debunking consistently reduces misperceptions and behavioral intentions for at least 1 week, while prebunking was less effective. Expert corrections only outperform non-expert corrections in reducing misperceptions in wave 1. In general, AI cues do not significantly influence the effectiveness of a correction, offering both opportunities and challenges for organizations hoping to automate corrections.
Funding Information
  • University of Minnesota

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