Emotional attachment to artificial intelligence and perceived social isolation among university students: An application of Sternberg’s triangular theory of love

Artificial intelligence (AI) has been progressively incorporated into numerous facets of student life, especially within educational settings where emotional involvement is essential for learning results. As AI systems advance to replicate sympathetic and engaging behaviors, inquiries arise about the emotional connections pupils establish with these technologies and the prospective function of AI in mitigating social isolation. This study examines university students' emotional attachment to AI via Sternberg's triangular theory of love—evaluating passion, closeness, and commitment—while also exploring students' perceptions of AI's emotional comprehension and feelings of social isolation. This cross-sectional study included 526 students from three prominent universities in Hanoi, Vietnam. Emotional attachment to the AI was evaluated via modified scales that assess the components of love, the emotional understanding of the AI, and the degree of perceived social isolation. The data were examined via descriptive statistics to assess emotional response levels and their variability. Students showed moderate levels of passion (M = 3.34, SD = 1.05), commitment (M = 3.39), and intimacy (M = 3.49, SD = 0.947) toward AI. They perceived AI as moderately capable of understanding emotions (M = 3.96, SD = 0.95), especially recognizing positive states. Perceived social isolation was relatively high (M = 3.57, SD = 1.17), with many students reporting challenges in confiding in or relying on family and peers. The variability across responses indicates that personal characteristics and disciplinary background may influence these perceptions. University students exhibit a developing emotional connection with AI, marked by moderate involvement yet limited closeness. Although AI has demonstrated promise as an emotional support agent, particularly for socially isolated individuals, it has not yet supplanted human interaction. These findings underscore the necessity for the advancement of emotionally intelligent AI systems that can proficiently enhance student well-being while preserving interpersonal ties.

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Publication Details

Journal
Multidisciplinary Science Journal
Published
2025-06-22
DOI
https://doi.org/10.31893/multiscience.2025662
Citations
1
Primary Topic
Death Anxiety and Social Exclusion
Type
article
Field-Weighted Citation Impact
2.44
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article

Emotional attachment to artificial intelligence and perceived social isolation among university students: An application of Sternberg’s triangular theory of love

Thang Van Le, Anh Thi Van Dam, Nam Hoang Le, Hue Thi Nguyen et al.
1 citations
Multidisciplinary Science Journal
Death Anxiety and Social Exclusion
2.44
article

Emotional attachment to artificial intelligence and perceived social isolation among university students: An application of Sternberg’s triangular theory of love

Thang Van Le, Anh Thi Van Dam, Nam Hoang Le, Hue Thi Nguyen, Thuy Thi Bich Tran, Thao Thi Nguyen, Anh Tuan Nguyen
article en
1 citations

Abstract

Artificial intelligence (AI) has been progressively incorporated into numerous facets of student life, especially within educational settings where emotional involvement is essential for learning results. As AI systems advance to replicate sympathetic and engaging behaviors, inquiries arise about the emotional connections pupils establish with these technologies and the prospective function of AI in mitigating social isolation. This study examines university students' emotional attachment to AI via Sternberg's triangular theory of love—evaluating passion, closeness, and commitment—while also exploring students' perceptions of AI's emotional comprehension and feelings of social isolation. This cross-sectional study included 526 students from three prominent universities in Hanoi, Vietnam. Emotional attachment to the AI was evaluated via modified scales that assess the components of love, the emotional understanding of the AI, and the degree of perceived social isolation. The data were examined via descriptive statistics to assess emotional response levels and their variability. Students showed moderate levels of passion (M = 3.34, SD = 1.05), commitment (M = 3.39), and intimacy (M = 3.49, SD = 0.947) toward AI. They perceived AI as moderately capable of understanding emotions (M = 3.96, SD = 0.95), especially recognizing positive states. Perceived social isolation was relatively high (M = 3.57, SD = 1.17), with many students reporting challenges in confiding in or relying on family and peers. The variability across responses indicates that personal characteristics and disciplinary background may influence these perceptions. University students exhibit a developing emotional connection with AI, marked by moderate involvement yet limited closeness. Although AI has demonstrated promise as an emotional support agent, particularly for socially isolated individuals, it has not yet supplanted human interaction. These findings underscore the necessity for the advancement of emotionally intelligent AI systems that can proficiently enhance student well-being while preserving interpersonal ties.

Multidisciplinary Science JournalVol. 7(12)
Hanoi National University of Education (VN), Bình Dương University (VN), Ho Chi Minh National Academy of Politics (VN), Thu Dau Mot University
Openalex Percentile: Top 12%
Death Anxiety and Social Exclusion
2.44
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