I love you, my AI companion! do you? perspectives from triangular theory of love and attachment theory
Ng, P. M.L., Wan, C., Lee, D., Garnelo-Gomez, I.
It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1108/INTR-11-2024-1783 Abstract/SummaryThis study examines the influence of artificial intelligence (AI) companions on users’ social well-being by integrating the Triangular Theory of Love and Attachment Theory. Specifically, this study explores how the three components of love (including intimacy, passion and commitment) shape users’ attachment (interactive engagement, emotional attachment, emotional trust) toward AI companions, and how attachment, in turn, impacts social well-being. The study also investigates the moderating role of sweet deception in these relationships. An online survey was conducted with 527 users of AI companion apps, recruited through a panel service provided by a marketing agency. The proposed path relationships in the conceptual framework were analyzed using SmartPLS 4.0. The results show that the three components of love significantly impact users’ attachment, and both interactive and emotional attachment subsequently influence social well-being. Additionally, sweet deception was found to strengthen the relationships between interactive engagement and social well-being, as well as that between emotional attachment and social well-being. This study makes a unique contribution to the literature by empirically examining how human-AI companion relationships impact users’ social well-being. Specifically, it introduces the novel concept of sweet deception – the strategic use of affectionate yet deceptive communications to foster emotional bonds – and empirically test its role in strengthening the relationship between users’ emotional attachment and social well-being. By integrating Triangular Theory of Love and Attachment Theory, this study offers a new theoretical framework for understanding the emotional dynamics of human-AI interactions. Moreover, this study provides innovative practical insights for businesses on designing emotionally engaging AI companions that promote user well-being.
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