Social workers' evaluation of ChatGPT for solving ethical dilemmas within the limits of confidentiality.
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| Title: | Social workers' evaluation of ChatGPT for solving ethical dilemmas within the limits of confidentiality. |
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| Authors: | Segal, Michal (AUTHOR) |
| Source: | Journal of Social Work Practice. Mar2026, Vol. 40 Issue 1, p5-18. 14p. |
| Subjects: | Violence prevention, Generative artificial intelligence, Empathy, Social workers, Professional ethics, Qualitative research, Privacy, Clinical decision support systems, Legal liability, Research evaluation, Ethical problems, Social worker attitudes, Emotions, Problem solving, Social case work, Ethical decision making, Students, Thematic analysis, Trust, Phenomenology, Therapeutic alliance, Judgment (Psychology), Medical ethics, Professional competence, Disclosure |
| Abstract: | This study examined how social workers evaluate the use of ChatGPT in solving ethical dilemmas related to confidentiality in social work. The study employed qualitative document analysis based on a phenomenological approach, analysing assignments of 70 master's degree students in social work. Participants compared their own solutions to ethical dilemmas with those proposed by ChatGPT. The analysis revealed three main issues: disparities in analysing complex professional dilemmas, differences in reference to ethical codes and laws, and disparities in emotional aspects and empathy. Study participants perceived their responses as more comprehensive, legally based, and empathetic compared to ChatGPT's solutions, which were perceived as superficial and lacking emotional understanding. While ChatGPT offers potential as a supportive tool, it cannot replace social workers' ethical judgement and empathy. Recommendations include developing AI training workshops and examining AI tools for ethical training while maintaining the profession's human element. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Social Work Practice is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
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