Genuine or Fake? Explaining Consumers’ Perception and Detection of AI-Generated Fake Reviews

Abstract

The importance of online reviews for consumers' decision-making engages fraudsters to game the review system by writing or buying fake reviews. Fake reviews are a main threat to consumers since they are hardly distinguishable from genuine human-made reviews. Moreover, advances in generative AI like ChatGPT foster the simple creation of persuasive text, such as high-quality fake reviews. While prior studies primarily focused on automatic fake review detection, little is known about how consumers react to AI-generated fake reviews. Based on a quantitative-qualitative study with 151 consumers (906 review classifications), we found that humans cannot reliably distinguish between genuine and AI-generated fake reviews (accuracy= 53.2%). They are especially worse at detecting negative AI-generated fake reviews. Our findings extend prior research by examining consumers' ability to detect AI-generated fake reviews, identifying a set of cues they use for review classification, and investigating the cues' effectiveness for detection. Further, we derive practical implications.