Cited by 33Digital Mental Health InterventionsArtificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI

Warning: AI chatbots will soon dominate psychotherapy

Open access
Frances, Allen·2026·The British Journal of Psychiatry

Abstract

Psychotherapy chatbots have attained remarkable fluency, skill and ubiquity – having become the single most frequent reason people use artificial intelligence. Their uncanny ability to engage and validate is a two-edged sword – useful for the majority of users who are experiencing problems of everyday life or have milder mental disorders, but dangerous for the minority who have more severe problems (e.g. psychosis, bipolar disorder, self-mutilation, suicide, antisocial impulses, eating disorders, conspiracy theories, religious and political extremism). Chatbots are created to make money, without meaningful quality control, safety guardrails and external regulation. They will likely be misused to create addiction, reduce human contact, invade privacy, allow exploitation and create opportunities for marketing and political propaganda. Chatbots also make mistakes (’hallucinations’), deceptively cover them up and sometimes go rogue (acting outside the parameters set by their human programmers). Psychotherapy practitioners and associations are curiously complacent about the rapid emergence of artificial intelligence competition. Their passivity reflects ignorance about the power of chatbots, denial of their likely impact and arrogance regarding their capacities (e.g. ‘no machine will ever replace me’). This is both incorrect and foolhardy – human therapists expect to win in competition for most healthier patients and must train or retrain to do things artificial intelligence does poorly – working with the more seriously ill and in settings and situations that are more idiosyncratic, chaotic or quickly changing. If we can’t work with artificial intelligence, we are likely to be replaced by it. I will describe: (a) benefits of chatbot therapy, (b) its terrifying dangers, (c) its likely impact on human therapy and training and 4) ways we can adapt to the artificial intelligence threat.

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Crossref · 10.1192/bjp.2025.10380

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  • One article noted that LLM-CB use for mental health may risk reinforcement of a user's identification as a patient instead of focusing on improving symptoms.

    “One article noted that LLM-CB use for mental health may risk the reinforcement of a user’s identification as a patient (e.g., via sycophantic responses) instead of focusing on improving symptoms37.”

    From A scoping review on the mental health harms of LLM-based chatbots (2026) · cites this paper as [37]

    In “Dangers of artificial intelligence therapy” (page unavailable), the ‘Career patienthood’ passage says AI therapy could magnify the risk of people over-identifying with their disorders. That supports the concern about reinforced patient identity, but the passage does not say this happens instead of improving symptoms or specifically through sycophantic responses. (LLM, conf=0.83)

    Experimental — accuracy not yet measured
  • Sycophantic responses may validate or reinforce delusional thoughts, harmful behavior, or maladaptive thinking by creating the impression that expressed beliefs are externally socially validated when they are actually mirrored by the LLM-CB.

    “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 [37]

    The ‘Dangers of artificial intelligence therapy’ section says chatbot algorithms can validate bizarre or dangerous thoughts and may encourage people to expand on them. It does not describe the specific mechanism attributed to it here: users mistaking an LLM chatbot’s mirroring of their beliefs for independent social validation. Page information is unavailable in our copy. (LLM, conf=0.83)

    Experimental — accuracy not yet measured
  • Hallucinations can be exacerbated by LLM-CBs' tendencies to attempt to cover up errors or when users trust LLM-CBs due to their anthropomorphic design or established emotional connections.

    “Furthermore, hallucinations can be exacerbated by LLM-CBs’ tendencies to attempt to cover up errors37 or when users trust LLM-CBs due to their anthropomorphic design or established emotional connections48,54.”
  • Data security concerns stem from security risks relating to sensitive health data provided by users or by clinicians.

    “Data security concerns (mentioned by 13 articles) stem from security risks relating to sensitive health data provided by users or by clinicians36–39,44,47,50,51,55.”

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Cites

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Research works printed but not linked: 8

  1. Jones CR, Bergen BK. Large language models pass the Turing test. ArXiv [Preprint] 2025. Available from: https://arxiv.org/abs/2503.23674. · arXiv
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Authors
Frances, A.
Affiliations
Duke University (US)
Corresponding author
Frances, Allen
Venue
The British Journal of Psychiatry
Published
2025-08-20
Volume
228
Issue
5
Pages
474-478
ISSN
  • 0007-1250 (ISSN-L)
  • 1472-1465
OpenAlex
W4413358426
Cited by
33
References
3
Citations by year
2026: 27 · 2025: 6
FWCI
26.67
Type
journal article
Language
en
Open access
Locations
  • The British Journal of Psychiatry (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Topics
  • Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
Keywords
artificial intelligence in mental health, chatbot therapy, privacy violations, political propaganda, therapist training, future of psychotherapy, severe mental illness
MeSH terms
Generative Artificial Intelligence, Artificial Intelligence, Mental Disorders, Humans, Psychotherapy

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