The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.
Artificial Intelligence in Social Work: Emerging Ethical Issues
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Archives > Volume 20 (2023) > Issue 2 > Item 05 DOI: 10.55521/10-020-205 Frederic G. Reamer, Ph.D. Rhode Island College freamer@ric.edu Full disclosure: Frederic G. Reamer is a member of the IJSWVE editorial board. IJSWVE uses an anonymous review process in which authors do not review their own work and reviewers do not know authors’ identities. Reamer, F. (2023). Artificial Intelligence […]
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A social worker relying on flawed AI outputs to inform a clinical assessment, treatment plan, or policy recommendation would provide substandard service and commit a profound failure of professional judgment and a significant ethical breach.
“A social worker relying on such flawed outputs to inform a clinical assessment, a treatment plan, or a policy recommendation would not only be providing substandard service but would be committing a profound failure of professional judgment and a significant ethical breach (National Association of Social Workers, 2021; Reamer, 2023).”
From Paying the Cognitive Debt: An Experiential Learning Framework for Integrating AI in Social Work Education (2025) · cites this paper as Reamer, 2023
The Client misdiagnosis section says social workers should supplement AI-generated assessments with independent judgment and warns that misdiagnosis may cause harm. The guidance on using AI results likewise says AI should supplement, not replace, professional judgment. These passages support the concern about relying on flawed outputs, but they do not establish that doing so in every clinical or policy context would constitute a profound failure of judgment and a significant ethical breach. (LLM, conf=0.84)
Experimental — accuracy not yet measuredSocial workers' expertise in systems thinking, social justice, and the dignity and worth of the person is needed to identify and mitigate algorithmic biases that can harm vulnerable populations.
“Social workers' expertise in systems thinking, social justice, and the dignity and worth of the person is desperately needed to identify and mitigate the algorithmic biases that can harm vulnerable populations (Reamer, 2023).”
From Paying the Cognitive Debt: An Experiential Learning Framework for Integrating AI in Social Work Education (2025) · cites this paper as Reamer, 2023
The discussion of algorithmic bias says AI used in social work can incorporate bias affecting vulnerable or protected groups, and the Conclusion urges social workers to evaluate AI for algorithmic bias. The paper does not specifically identify systems thinking, social justice, and respect for the dignity and worth of the person as the expertise needed to detect and mitigate that bias (no page numbers supplied). (LLM, conf=0.84)
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Cites
Code of Ethics of the National Association of Social Workers
Clifton, L. (2014) · Encyclopedia of Human Services and Diversity · doi:10.4135/9781483346663.n105 · Cited by 822
Artificial Intelligence in Healthcare: Review and Prediction Case Studies
Rong, G., Mendez, A., Assi, E. B., Zhao, B., & Sawan, M. (2020) · Engineering · doi:10.1016/j.eng.2019.08.015 · Cited by 590
Code of Ethics of the National Association of Social Workers
(2005) · Journal of Aggression Maltreatment & Trauma · doi:10.1300/j146v11n03_06 · Cited by 368
Kwok, S. M. (2015) · China Journal of Social Work · doi:10.1080/17525098.2015.1082488 · Cited by 204
Artificial Intelligence in Behavioral and Mental Health Care
(2016) · Elsevier eBooks · doi:10.1016/c2013-0-12824-3 · Cited by 117
Keddell, E. (2019) · Social Sciences · doi:10.3390/socsci8100281 · Cited by 109
iHealth: The ethics of artificial intelligence and big data in mental healthcare
Rubeis, G. (2022) · Internet Interventions · doi:10.1016/j.invent.2022.100518 · Cited by 105
Can Predictive Algorithms Assist Decision‐Making in Social Work with Children and Families?
Gillingham, P. (2019) · Child Abuse Review · doi:10.1002/car.2547 · Cited by 99
Terra, M., Baklola, M. I., Ali, S. A. A., & El-Bastawisy, K. (2023) · The Egyptian Journal of Neurology Psychiatry and Neurosurgery · doi:10.1186/s41983-023-00681-z · Cited by 88
Ethical Standards in Social Work: A Review of the NASW Code of Ethics
Reamer, F. G. (1998) · Cited by 87
Self-citationAsakura, K., Occhiuto, K., Todd, S., Leithead, C., & Clapperton, R. (2020) · Journal of Teaching in Social Work · doi:10.1080/08841233.2020.1813234 · Cited by 80
Challenges for Artificial Intelligence in Recognizing Mental Disorders
Yan, W., Ruan, Q.-N., & Jiang, K. (2022) · Diagnostics · doi:10.3390/diagnostics13010002 · Cited by 79
Artificial Intelligence and Social Work
(2018) · doi:10.1017/9781108669016 · Cited by 75
Ethics and Values in Social Work: An Integrated Approach for a Comprehensive Curriculum
Congress, E. P. (2020) · Journal of Teaching in Social Work · doi:10.1080/08841233.2020.1714405 · Cited by 71
Social Work and Artificial Intelligence: Into the Matrix
Goldkind, L. (2021) · Social Work · doi:10.1093/sw/swab028 · Cited by 62
Using Machine Learning in Burnout Prediction: A Survey
Grządzielewska, M. (2021) · Child and Adolescent Social Work Journal · doi:10.1007/s10560-020-00733-w · Cited by 46
Rice, E. R. W., Yoshioka‐Maxwell, A., Petering, R., et al. (2018) · Journal of the Society for Social Work and Research · doi:10.1086/701439 · Cited by 44
Challenges in Using Big Data to Develop Decision Support Systems for Social Work in Germany
Schneider, D., & Seelmeyer, U. (2019) · Journal of Technology in Human Services · doi:10.1080/15228835.2019.1614513 · Cited by 44
The Routledge International Handbook of Digital Social Work
Peláez, A. L., & Kirwan, G. (2023) · Routledge eBooks · doi:10.4324/9781003048459 · Cited by 41
Pascoe, K. M. (2021) · International Social Work · doi:10.1177/0020872820980833 · Cited by 31
Functions, Utilities and Limitations: A Scoping Study of Decision Support Algorithms in Social Work
Jacobi, C. B., & Christensen, M. (2023) · Journal of Evidence-Based Social Work · doi:10.1080/26408066.2022.2159777 · Cited by 30
Lanier, P. J., Rodriguez, M., Verbiest, S., Bryant, K., Guan, T., & Zolotor, A. (2019) · Journal of Family Violence · doi:10.1007/s10896-019-00074-y · Cited by 25
The Use of Decision Support Systems in Social Work: A Scoping Study Literature Review
Liedgren, P., Elvhage, G., Ehrenberg, A., et al. (2015) · Journal of Evidence-Informed Social Work · doi:10.1080/15433714.2014.914992 · Cited by 22
Developing a statistical model for assessment of referrals of children at risk
Søbjerg, L. M. (2022) · Child Abuse Review · doi:10.1002/car.2749 · Cited by 8
The Routledge international handbook of digital social work
Kardawi, M. Y., & Simanjuntak, M. E. (2024) · Journal of Human Behavior in the Social Environment · doi:10.1080/10911359.2024.2425770 · Cited by 7
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Research works printed but not linked: 1
- Reamer, F. (2023a). Risk management in the behavioral health professions: A practical guide to preventing malpractice and licensing-board com- plaints. Columbia University Press.
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Watts, K. J. (2025) · Education Sciences · doi:10.3390/educsci15101304 · Cited by 18
Metadata
- Authors
- Reamer, F. G.
- Affiliations
- Rhode Island College (US)
- Corresponding author
- Reamer, Frederic G.
- ORCID
- Reamer, Frederic G.
- Venue
- International Journal of Social Work Values and Ethics
- Published
- 2023-10-30
- Volume
- 20
- Issue
- 2
- Pages
- 52-71
- ISSN
- 1553-6947 (ISSN-L)
- 2790-6345
- OpenAlex
- W4388023343
- Cited by
- 150
- References
- 25
- Citations by year
- 2026: 83 · 2025: 50 · 2024: 16
- FWCI
- 37.20
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- International Journal of Social Work Values and Ethics (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Social Sciences › Public Administration › Social Work Education and Practice
- Social Sciences › Law › Artificial Intelligence in Law
- Keywords
- artificial intelligence, social work ethics
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