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Using attachment theory to conceptualize and measure the experiences in human-AI relationships
Abstract
Artificial intelligence (AI) is growing “stronger and wiser,” leading to increasingly frequent and varied human-AI interactions. This trend is expected to continue. Existing research has primarily focused on trust and companionship in human-AI relationships, but little is known about whether attachment-related functions and experiences could also be applied to this relationship. In two pilot studies and one formal study, the current project first explored using attachment theory to examine human-AI relationships. Initially, we hypothesized that interactions with generative AI mimic attachment-related functions, which we tested in Pilot Study 1. Subsequently, we posited that experiences in human-AI relationships could be conceptualized via two attachment dimensions, attachment anxiety and avoidance, which are similar to traditional interpersonal dynamics. To this end, in Pilot Study 2, a self-report scale, the Experiences in Human-AI Relationships Scale, was developed. Further, we tested its reliability and validity in a formal study. Overall, the findings suggest that attachment theory significantly contributes to understanding the dynamics of human-AI interactions. Specifically, attachment anxiety toward AI is characterized by a significant need for emotional reassurance from AI and a fear of receiving inadequate responses. Conversely, attachment avoidance involves discomfort with closeness and a preference for maintaining emotional distance from AI. This implies the potential existence of shared structures underlying the experiences generated from interactions, including those with other humans, pets, or AI. These patterns reveal similarities with human and pet relationships, suggesting common structural foundations. Future research should examine how these attachment styles function across different relational contexts.
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“Traditional scales assume unidirectional relationships, but adolescents often perceive AI agents as responsive and human-like even when no true reciprocity exists [141].”
From Understanding Teen Overreliance on AI Companion Chatbots Through Self-Reported Reddit Narratives (2026) · cites this paper as [141]
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Romantic love conceptualized as an attachment process.
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“These features are similar to the characteristics of attachment figures proposed by attachment theory, which emphasizes safe haven and secure base functions (Bowlby, 1969 ; Hazan & Shaver, 1987 ; Mikulincer & Shaver, 2023).”
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“Moreover, validating the findings of the present research using larger and more diverse samples would enhance the generalizabil - ity and applicability of the research (Simons et al., 2017), providing a robust basis for future technological innovation and theoretical development.”
Human- versus Artificial Intelligence
Korteling, J. E. (., van de Boer-Visschedijk, G. C., Blankendaal, R. A. M., Boonekamp, R. C., & Eikelboom, A. R. (2021) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2021.622364 · Cited by 619 · cited 1×
“AI technologies (e.g., ChatGPT) have been developing rapidly, becoming increasingly anthropomorphic and “wiser and stronger” than human beings in various fields (Kim & Im, 2023 ; Korteling et al., 2021).”
Attachment and trust in artificial intelligence
Gillath, O., Ai, T., Branicky, M. S., Keshmiri, S., Davison, R. B., & Spaulding, R. (2021) · Computers in Human Behavior · doi:10.1016/j.chb.2020.106607 · Cited by 448 · cited 1×
“Many studies have provided insights into human-AI trust (e.g., Gillath et al., 2021) and the emotional and affective functions of AI (e.g., Astell & Clayton, 2024).”
AI can help people feel heard, but an AI label diminishes this impact
Yin, Y., Jia, N., & Wakslak, C. J. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2319112121 · Cited by 247
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Astell, A., & Clayton, D. (2024) · Frontiers in Psychology · doi:10.3389/fpsyg.2024.1320555 · Cited by 12
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Cited by
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Understanding Teen Overreliance on AI Companion Chatbots Through Self-Reported Reddit Narratives
Namvarpour, M. (., Brofsky, B., Medina, J. Y., Akter, M., & Razi, A. (2026) · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3790597 · Cited by 24
Yang, X. (2026) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2026.2618548 · Cited by 3
Metadata
- Authors
- Yang, F., & Oshio, A.
- Venue
- Current Psychology
- Published
- 2025-05-09
- Volume
- 44
- Issue
- 11
- Pages
- 10658-10669
- ISSN
- 1046-1310
- 1936-4733
- Cited by
- 63
- References
- 9
- Language
- en
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