When ELIZA meets therapists: A Turing test for the heart and mind

"Can machines be therapists?" is a question receiving increased attention given the relative ease of working with generative artificial intelligence. Although recent (and decades-old) research has found that humans struggle to tell the difference between responses from machines and humans, recent findings suggest that artificial intelligence can write empathically and the generated content is rated highly by therapists and outperforms professionals. It is uncertain whether, in a preregistered competition where therapists and ChatGPT respond to therapeutic vignettes about couple therapy, a) a panel of participants can tell which responses are ChatGPT-generated and which are written by therapists (N = 13), b) the generated responses or the therapist-written responses fall more in line with key therapy principles, and c) linguistic differences between conditions are present. In a large sample (N = 830), we showed that a) participants could rarely tell the difference between responses written by ChatGPT and responses written by a therapist, b) the responses written by ChatGPT were generally rated higher in key psychotherapy principles, and c) the language patterns between ChatGPT and therapists were different. Using different measures, we then confirmed that responses written by ChatGPT were rated higher than the therapist's responses suggesting these differences may be explained by part-of-speech and response sentiment. This may be an early indication that ChatGPT has the potential to improve psychotherapeutic processes. We anticipate that this work may lead to the development of different methods of testing and creating psychotherapeutic interventions. Further, we discuss limitations (including the lack of the therapeutic context), and how continued research in this area may lead to improved efficacy of psychotherapeutic interventions allowing such interventions to be placed in the hands of individuals who need them the most.

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Publication Details

Journal
PLOS mental health.
Published
2025-02-12
DOI
https://doi.org/10.1371/journal.pmen.0000145
Citations
40
Primary Topic
Psychotherapy Techniques and Applications
Type
article
Field-Weighted Citation Impact
92.27
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article

When ELIZA meets therapists: A Turing test for the heart and mind

Lane L. Ritchie, Shayna Guttman, Karen Rothman, Zachary T. Goodman et al.
40 citations
PLOS mental health.
Psychotherapy Techniques and Applications
92.27
article

When ELIZA meets therapists: A Turing test for the heart and mind

Lane L. Ritchie, Shayna Guttman, Karen Rothman, Zachary T. Goodman, Benjamin M. Bailey, Steven M. Harris, Stephen Hatch, R. Scott Braithwaite, H. Dorian Hatch, P. R. O’Connell, David Nicholas Top, Daniel P. Holt, Yunying Le, Laura M. Vowels, Charlotte Esplin, Merranda McLaughlin, Russell J. Bailey, Alyssa L. Brown
article en
40 citations

Abstract

No abstract available for this paper.

PLOS mental health.Vol. 2(2)
Brigham Young University (US), University of Minnesota (US), University of Denver (US), University of Miami (US), Sam Houston State University (US), Utah Valley University (US), New York City Department of Transportation (US), Pontifical John Paul II Institute for Studies on Marriage and Family (US), University of California San Diego (US), Massachusetts General Hospital (US), Twin Cities Orthopedics (US), Mental Health America (US), The Ohio State University (US), University of Lausanne (CH)
Openalex Percentile: Top 0%
Psychotherapy Techniques and Applications
92.27
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