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Hysteria in empathy: Understanding virtual companionship and emotional connection between humans and Al

Guo, Minling, Liu, Zhiming·2025·Theory & Psychology
DOI 10.1177/09593543251319738
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Abstract

Increasing numbers of people tend to seek relationships with artificial intelligence (AI) because of its comprehensive mastery of knowledge. This research reveals that ChatGPT has become a temporary refuge for individuals encountering real-life emotional crises. The communicative affordance of human–AI conversation is featured by logos-centrism, pursuing the identity of language and essence between humans and technology. Grounded in Lacanian discourse theory, this research argues that the psychological and discursive dynamics behind human–AI dialogue entail a structure of the hysteric’s discourse , which stems from the questioning users fantasizing and interrogating the GPT as a master of knowledge. Also, capitalist discourse is revealed during the repetitive AI companionship that empowers users with the agency of controlling the dialogue and the user’s primordial lack of desire is transformed into a demand that can be resolved through consumption. GPT may become a consumer product of technological capital, while the emotional needs of individuals are commodified within these discursive structures.

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  • Critical and phenomenological arguments focus on the lack of genuine empathy, understanding, emotional depth, recognition or reciprocity in human-AI relationships.

    “Critical and phenomenological arguments also focus on the lack of genuine empathy, understanding, emotional depth, recognition or reciprocity in human-AI relationships (Wiederhold, 2024;Li & Zhang, 2024;Guo & Liu, 2025;Symonds & Sanwoolu, 2025;Zhang et al., 2025).”

    From Artificial intelligence and unconditional love: the rise of generative AI as an alternative form of mental health support (2026) · cites this paper as Guo & Liu, 2025

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Metadata

Authors
Guo, M., & Liu, Z.
Venue
Theory & Psychology
Publisher
SAGE Publications
Published
2025-02-24
Volume
35
Issue
2
Pages
163-184
ISSN
  • 0959-3543
  • 1461-7447
DOI
10.1177/09593543251319738
Cited by
12
References
9
Language
en
Licence
journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)

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