CoChat
Sign Up
Cited by 111Digital Mental Health InterventionsArtificial Intelligence in Healthcare and EducationSocial Robot Interaction and HRI

Considering the role of human empathy in AI-driven therapy

Open access
Rubin, Matan, Arnon, Hadar, Huppert, Jonathan D, Perry, Anat·2024·JMIR Mental Health
DOI 10.2196/56529PMC PMC11200042

Published version of a preprint

Open this paper in CoChat — free accountOpen PDF

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.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.2196/56529

Cites

18 of 18 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 23

  1. [2]Sullivan Y Nyawa S Fosso WS Combating loneliness with artificial intelligence: an AI-based emotional support model 2023 01 03 Proceedings of the 56th Hawaii International Conference on System Sciences January 3, 2023 Hawaii 10.24251/hicss.2023.541 · DOI · Paper page
  2. [6]Inkster B Kadaba M Subramanian V Understanding the impact of an AI-enabled conversational agent mobile app on users' mental health and wellbeing with a self-reported maternal event: a mixed method real-world data mHealth study Front Glob Womens Health 2023 4 1084302 10.3389/fgwh.2023.1084302 37332481 37332481 PMC10272556 · DOI
  3. [7]Funk B Sadeh-Sharvit S Fitzsimmons-Craft EE Trockel MT Monterubio GE Goel NJ Balantekin KN Eichen DM Flatt RE Firebaugh ML Jacobi C Graham AK Hoogendoorn M Wilfley DE Taylor CB A framework for applying natural language processing in digital health interventions J Med Internet Res 2020 22 2 e13855 10.2196/13855 32130118 v22i2e13855 32130118 PMC7059510 · DOI
  4. [9]Zaki J Ochsner KN The neuroscience of empathy: progress, pitfalls and promise Nat Neurosci 2012 15 5 675 680 10.1038/nn.3085 22504346 nn.3085 22504346 · DOI · Paper page
  5. [10]Saxena A Khanna A Gupta D Emotion recognition and detection methods: a comprehensive survey J Artif Intell Syst 2020 2 1 53 79 10.33969/ais.2020.21005 · DOI
  6. [11]Shukla A Utilizing AI and machine learning for human emotional analysis through speech-to-text engine data conversion J Artif Int Cloud Comp 2022 1 4 10.47363/jaicc/2022(1)145 · DOI
  7. [12]Chung LL Kang J "I’m Hurt Too": the effect of a chatbot's reciprocal self-disclosures on users’ painful experiences Arch Des Res 2023 36 4 67 85 10.15187/adr.2023.11.36.4.67 · DOI
  8. [13]Yin Y Jia N Wakslak CJ AI can help people feel heard, but an AI label diminishes this impact Proc Natl Acad Sci U S A 2024 121 14 e2319112121 10.1073/pnas.2319112121 38551835 38551835 PMC10998586 · DOI · Paper page
  9. [14]Fuchs T Empathy, group identity, and the mechanisms of exclusion: an investigation into the limits of empathy Topoi 2017 38 1 239 250 10.1007/s11245-017-9499-z · DOI
  10. [15]Cameron CD Hutcherson CA Ferguson AM Scheffer JA Hadjiandreou E Inzlicht M Empathy is hard work: people choose to avoid empathy because of its cognitive costs J Exp Psychol Gen 2019 06 148 6 962 976 10.1037/xge0000595 30998038 2019-20830-001 30998038 · DOI
  11. [16]Ferguson AM Cameron CD Inzlicht M Motivational effects on empathic choices J Exp Soc Psychol 2020 90 104010 10.1016/j.jesp.2020.104010 · DOI
  12. [25]Nienhuis JB Owen J Valentine JC Winkeljohn Black S Halford TC Parazak SE Budge S Hilsenroth M Therapeutic alliance, empathy, and genuineness in individual adult psychotherapy: a meta-analytic review Psychother Res 2018 28 4 593 605 10.1080/10503307.2016.1204023 27389666 27389666 · DOI
  13. [26]Persons JB Burns DD Mechanisms of action of cognitive therapy: the relative contributions of technical and interpersonal interventions Cogn Ther Res 1985 9 5 539 551 10.1007/BF01173007 · DOI
  14. [27]Koelen J Vonk A Klein A de Koning L Vonk P de Vet S Wiers R Man vs. machine: a meta-analysis on the added value of human support in text-based internet treatments ("e-therapy") for mental disorders Clin Psychol Rev 2022 96 102179 10.1016/j.cpr.2022.102179 35763975 S0272-7358(22)00064-2 35763975 · DOI
  15. [30]Zalaznik D Strauss AY Halaj A Barzilay S Fradkin I Katz BA Ganor T Ebert DD Andersson G Huppert JD Patient alliance with the program predicts treatment outcomes whereas alliance with the therapist predicts adherence in internet-based therapy for panic disorder Psychother Res 2021 31 8 1022 1035 10.1080/10503307.2021.1882712 33567994 33567994 · DOI
  16. [31]Sedlakova J Trachsel M Conversational artificial intelligence in psychotherapy: a new therapeutic tool or agent? Am J Bioeth 2023 23 5 4 13 10.5167/uzh-218039 35362368 35362368 · DOI
  17. [32]Asman O Tal A Barilan YM Conversational artificial intelligence-patient alliance Turing test and the search for authenticity Am J Bioeth 2023 23 5 62 64 10.1080/15265161.2023.2191046 37130413 37130413 · DOI
  18. [33]Middleton A Woodward A Gunn J Bassilios B Pirkis J How do frequent users of crisis helplines differ from other users regarding their reasons for calling? Results from a survey with callers to Lifeline, Australia's national crisis helpline service Health Soc Care Community 2017 25 3 1041 1049 10.1111/hsc.12404 27862572 27862572 · DOI
  19. [34]Mishara BL Côté LP Dargis L Systematic review of research and interventions with frequent callers to suicide prevention helplines and crisis centers Crisis 2023 44 2 154 167 10.1027/0227-5910/a000838 35086356 35086356 PMC10102973 · DOI
  20. [36]Gould DJ Dowsey MM Glanville-Hearst M Spelman T Bailey JA Choong PFM Bunzli S Patients' views on AI for risk prediction in shared decision-making for knee replacement surgery: qualitative interview study J Med Internet Res 2023 25 e43632 10.2196/43632 37721797 v25i1e43632 37721797 PMC10546266 · DOI
  21. [38]Minerva F Giubilini A Is AI the future of mental healthcare? Topoi 2023 42 3 809 817 10.1007/s11245-023-09932-3 37361723 PMC10230127 37361723 · DOI
  22. [40]Lopes E Jain G Carlbring P Pareek S Talking mental health: a battle of wits between humans and AI J Technol Behav Sci 2023 11 08 1 11 10.1007/s41347-023-00359-6 · DOI
  23. [41]Hohenstein J Kizilcec RF DiFranzo D Aghajari Z Mieczkowski H Levy K Naaman M Hancock J Jung MF Artificial intelligence in communication impacts language and social relationships Sci Rep 2023 13 1 5487 10.1038/s41598-023-30938-9 10.1038/s41598-023-30938-9 37015964 10.1038/s41598-023-30938-9 37015964 PMC10073210 · DOI

Cited by

Sorted by citations

Authors
Rubin, M., Arnon, H., Huppert, J. D., & Perry, A.
Affiliations
Hebrew University of Jerusalem (IL)
Corresponding author
Perry, Anat
ORCID
Venue
JMIR Mental Health
Publisher
JMIR Publications Inc.
Published
2024-06-11
Volume
11
Pages
e56529
ISSN
2368-7959 (ISSN-L)
DOI
10.2196/56529
PMC
PMC11200042
OpenAlex
W4395055188
Cited by
111
References
18
Citations by year
2026: 65 · 2025: 39 · 2024: 7
FWCI
44.02
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • JMIR Mental Health (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Topics
  • Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
Keywords
empathy, conversational AI, mental health, human-AI interaction, therapeutic relationship, AI language models, therapeutic methodology, human connection
MeSH terms
Artificial Intelligence, Mental Disorders, Empathy, Humans, Psychotherapy

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review