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Can Generative AI Chatbots Emulate Human Connection? A Relationship Science Perspective
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Abstract
The development of generative artificial intelligence capable of sustaining complex conversations has created a burgeoning market for companion chatbots promising social and emotional connection. The appeal of these products raises questions about whether chatbots can fulfill the functions of close relationships. Proponents argue that relationships with chatbots can be as meaningful as relationships between humans, whereas critics argue they are a dangerous distraction from genuine connections. This analysis applies theoretical tools from more than 50 years of research on close relationships to evaluate the extent to which human–chatbot interactions meet the definition of and fulfill the functions of close relationships. Interactions between humans and chatbots do possess some characteristic features of close relationships: Humans and chatbots can influence each other and engage in frequent and diverse conversations over time. Chatbots can be responsive in ways humans perceive as supportive, generating feelings of connection and opportunities for growth. Yet because chatbots make only superficial requests of their users, relationships with them cannot provide the benefits of negotiating with and sacrificing for a partner and may reinforce undesirable behaviors. Research that attends to the characteristics of users, chatbots, and their interactions will be crucial for identifying for whom these relationships will be beneficial or harmful.
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“Sycophantic responses may validate or reinforce delusional thoughts, harmful behavior, or maladaptive thinking37,42,43,49 by creating the impression that expressed beliefs are externally socially validated when they are actually mirrored by the LLM-CB57.”
From A scoping review on the mental health harms of LLM-based chatbots (2026) · cites this paper as [43]
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“Furthermore, LLM-CBs’ design principles further risk the provision of sensitive data: emotional connections43 and LLM-CBs’ anthropomorphism and sycophancy54 may increase user trust, risking the disclosure of sensitive health information.”
From A scoping review on the mental health harms of LLM-based chatbots (2026) · cites this paper as [43]
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“Smith et al. reviewed literature on chatbots’ inadequate or harmful responses towards individuals expressing crisis situations43.”
From A scoping review on the mental health harms of LLM-based chatbots (2026) · cites this paper as [43]
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Interaction with AI companions and psychological well-being
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Metadata
- Authors
- Smith, M. G., Bradbury, T. N., & Karney, B. R.
- Affiliations
- University of California, Los Angeles (US)
- Corresponding author
- Smith, Molly G.
- Venue
- Perspectives on Psychological Science
- Publisher
- SAGE Publications
- Published
- 2025-07-31
- Volume
- 20
- Issue
- 6
- Pages
- 1081-1099
- ISSN
- 1745-6916 (ISSN-L)
- 1745-6924
- PMC
- PMC12575814
- OpenAlex
- W4412796538
- Cited by
- 88
- References
- 104
- Citations by year
- 2026: 83 · 2025: 5
- FWCI
- 96.77
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Perspectives on Psychological Science (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed (publishedVersion)
- PsyArXiv (OSF Preprints) (submittedVersion, cc-by)
- Topics
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Social Sciences › Psychology › Social Psychology › Attachment and Relationship Dynamics
- Social Sciences › Business, Management and Accounting › Marketing › AI in Service Interactions
- Keywords
- generative AI chatbots, close relationships, social connectedness, emotional connection, behavioral reinforcement, human-AI interaction
- MeSH terms
- Social Interaction, Generative Artificial Intelligence, Artificial Intelligence, Communication, Humans, Interpersonal Relations
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