Paper Type
ERF
Abstract
Artificial intelligence (AI) is increasingly integrated into fashion marketing and social media platforms, yet consumer responses to AI-generated versus human-generated imagery remain unclear. This study examines how content source influences visual attention and engagement behavior in fashion media contexts. Participants view curated Pinterest-style fashion boards while their eye movements and behavioral responses are recorded. Drawing on processing fluency, authenticity research, and Uncanny Valley theory, we predict that AI-generated images will attract greater visual scrutiny but elicit lower behavioral engagement than human-generated images. We further examine whether the presence of faces amplifies these differences. By integrating biometric measures with behavioral engagement outcomes, this research advances understanding of how consumers cognitively process and respond to AI-generated creative content. The findings contribute to the emerging discussions in HCI and NeuroIS on authenticity, technological mediation, and the strategic use of generative AI in digital fashion marketing environments.
Paper Number
1766
Recommended Citation
Voke, Ruby; McClanen-Clemons, Alaina; and Smith, Sawyer, "AI Fashion Media: When Visual Attention Diverges from Engagement" (2026). AMCIS 2026 Proceedings. 16.
https://aisel.aisnet.org/amcis2026/sig_hci/sig_hci/16
AI Fashion Media: When Visual Attention Diverges from Engagement
Artificial intelligence (AI) is increasingly integrated into fashion marketing and social media platforms, yet consumer responses to AI-generated versus human-generated imagery remain unclear. This study examines how content source influences visual attention and engagement behavior in fashion media contexts. Participants view curated Pinterest-style fashion boards while their eye movements and behavioral responses are recorded. Drawing on processing fluency, authenticity research, and Uncanny Valley theory, we predict that AI-generated images will attract greater visual scrutiny but elicit lower behavioral engagement than human-generated images. We further examine whether the presence of faces amplifies these differences. By integrating biometric measures with behavioral engagement outcomes, this research advances understanding of how consumers cognitively process and respond to AI-generated creative content. The findings contribute to the emerging discussions in HCI and NeuroIS on authenticity, technological mediation, and the strategic use of generative AI in digital fashion marketing environments.
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