1. How Does Acknowledging Users’ Preferences Impact AI’s Ability to Make Conflicting Recommendations?
- Author
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Marti, Deniz, Budathoki, Anjila, Ding, Yi, Lucas, Gale, and Nelson, David
- Abstract
AbstractArtificial intelligence (AI) decision support systems are crucial in modern decision-making processes. Their increasing human-like adaptability introduces challenges, especially when their recommendations, for whatever reason, need to conflict with user preferences. This study examines the communication strategies AI systems should employ when their recommendations conflict with user preferences. We explored this research question through a hypothetical future interface where ChatGPT offers travel recommendations populated on a map. An online survey-based experiment was conducted, presenting 160 participants with ChatGPT-generated travel recommendations displayed alongside Bing map visuals. We employed a mixed-method experimental design, combining both between-subjects and within-subjects approaches, to investigate the impact of conflicting recommendations and the acknowledgment of user preferences on the acceptance of these recommendations. This effect is especially pronounced when the AI system acknowledges users’ preferences yet still offers conflicting recommendations to them. Contrary to the expectation that acknowledging users’ preferences could buffer the impact of such conflicts, our observations indicate the contrary. The presence of conflict following acknowledgment of users’ preferences, significantly causes a backfire effect, leading users to reject the recommendations. These findings underscore the need for consideration of recommendation delivery strategies in AI decision support systems and offer insights for designing future user interfaces and user experience research in the realm of recommendations provided by AI decision-support systems. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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