Abstract

The spread of digital misinformation on social media poses profound societal challenges. Fact-checking labels have emerged as a prominent design intervention, yet their effectiveness remains inconsistent. This study examines how label provenance, attributed to either a human expert panel or an AI system, shapes responses among younger and older adults. We focus on user judgments and behavioural intentions when content aligns or conflicts with prior beliefs. A multi-method design combines an online experiment with a NeuroIS protocol employing eye-tracking and electrodermal activity to capture behavioural and affective responses. The anticipated findings will inform the design of age-responsive, AI-enabled fact-checking systems, advance theoretical understanding of human–AI collaboration in the context of digital media, and provide actionable insights for building a more resilient and trustworthy digital information ecosystem.

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