Considering the Role of Human Empathy in AI-Driven Therapy

Matan Rubin, Hadar Arnon, Jonathan D. Huppert, Anat Perry*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

5 Scopus citations

Abstract

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.

Original languageEnglish
Article numbere56529
JournalJMIR Mental Health
Volume11
DOIs
StatePublished - 2024

Bibliographical note

Publisher Copyright:
©Matan Rubin, Hadar Arnon, Jonathan D Huppert, Anat Perry.

Keywords

  • AI
  • algorithm
  • algorithms
  • artificial empathy
  • artificial intelligence
  • digital mental health
  • e-mental health
  • emotion
  • emotions
  • empathetic
  • empathic
  • empathy
  • internet-based therapy
  • machine learning
  • mental disease
  • mental diseases
  • mental health
  • mental illness
  • mental illnesses
  • model
  • models
  • mood disorder
  • mood disorders
  • practical model
  • practical models
  • predictive analytics
  • predictive model
  • predictive models
  • predictive system
  • therapy

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