AI & ML
Digital Nudge Effects in Optimal Stopping Games: Antagonistic Interactions in Layered Choice Architectures
arXiv cs.HC0 views
arXiv:2610.28154v1 Announce Type: new Abstract: Digital nudges have become a prominent area of research in human-centered interaction, yet little is known about how they interact when deployed together. This study examines the individual and combined effects of anchoring, salience, and social proof digital nudges on stopping behavior and outcome quality in a sequential decision task. Using a 2^3 between-subjects factorial design grounded in the secretary problem (N = 181), we find that (1) an anchor nudge significantly increased exploration rather than constraining it (b = 1.207, p = .017); (2) the salience nudge produced the smallest effect of any condition; and (3) combining the anchor and social proof nudges produced the worst outcome quality of any condition ($181.83 vs. $192.21 for anchor-only), with outcome quality declining monotonically as nudge count increased. These findings provide the first controlled evidence for a digital nudge crowding-out effect with direct implications for the ethical design of digital interfaces.
Source:https://arxiv.org/abs/2610.28154PreviousLooks Fine to Me: Understanding Oversight in Agentic InteractionsNextThe GenAI Who Knew Too Little: Revisiting Transactive Memory Systems in Human GenAI Collaboration
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