Considering the Role of Human Empathy in AI-Driven Therapy

Autor: Matan Rubin, Hadar Arnon, Jonathan D Huppert, Anat Perry
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: JMIR Mental Health, Vol 11, p e56529 (2024)
Druh dokumentu: article
ISSN: 2368-7959
DOI: 10.2196/56529
Popis: Recent breakthroughs in artificial intelligence (AI) language models have elevated the vision of using conversational AI support for mental health, with a growing body of literature indicating varying degrees of efficacy. In this paper, we ask when, in therapy, it will be easier to replace humans and, conversely, in what instances, human connection will still be more valued. We suggest that empathy lies at the heart of the answer to this question. First, we define different aspects of empathy and outline the potential empathic capabilities of humans versus AI. Next, we consider what determines when these aspects are needed most in therapy, both from the perspective of therapeutic methodology and from the perspective of patient objectives. Ultimately, our goal is to prompt further investigation and dialogue, urging both practitioners and scholars engaged in AI-mediated therapy to keep these questions and considerations in mind when investigating AI implementation in mental health.
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