Artificial Intelligence (AI) Literacy for Social Work: Implications for Core Competencies
Abstract
Artificial intelligence (AI) is fundamentally reshaping society, offering new opportunities while potentially intensifying socioeconomic inequalities. For social workers working with marginalized populations, understanding AI’s societal impact is crucial, even if they do not directly engage with AI tools. This invited paper explores how AI literacy—the knowledge and skills to understand, use, and critically evaluate AI systems—can enhance social workers’ ability to support communities navigating AI-driven changes. We review AI’s impacts and applications in social work, explore their implications for the profession, and discuss their effects on social work core competencies. Specifically, we discuss how each of the social work competencies should evolve in response to AI-driven societal changes to better prepare social workers to support affected communities. By embedding AI literacy into core competencies, social workers can better address emerging challenges and promote equity in an AI-influenced society.
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AI literacy is not merely a technical skill but an essential component of every core competency, from ethical behavior to engaging diversity.
“This approach is consistent with the emerging scholarly consensus that AI literacy is not merely a technical skill but an essential component of every core competency, from ethical behavior to engaging diversity (Ahn et al., 2025).”
From Paying the Cognitive Debt: An Experiential Learning Framework for Integrating AI in Social Work Education (2025) · cites this paper as Ahn et al., 2025
The written reflections and policy drafts produced through these assignments serve as tangible, assessable artifacts that demonstrate student mastery of core competencies.
“The written reflections and policy drafts produced through these assignments serve as tangible, assessable artifacts that demonstrate student mastery of these core competencies (Ahn et al., 2025).”
From Paying the Cognitive Debt: An Experiential Learning Framework for Integrating AI in Social Work Education (2025) · cites this paper as Ahn et al., 2025
The framework provides a mechanism for programs to demonstrate innovation and produce artifacts that map directly to EPAS core competencies.
“It provides a mechanism for programs to demonstrate innovation and to produce artifacts that map directly to EPAS core competencies, such as ethical behavior and engaging with diversity (Ahn et al., 2025; Rodriguez et al., 2024).”
From Paying the Cognitive Debt: An Experiential Learning Framework for Integrating AI in Social Work Education (2025) · cites this paper as Ahn et al., 2025
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Watts, K. J. (2025) · Education Sciences · doi:10.3390/educsci15101304 · Cited by 18 · see citing works
- Authors
- Ahn, E., Choi, M., Fowler, P., & Song, I. H.
- Affiliations
- Washington University in St. Louis (US)
- Korea Advanced Institute of Science and Technology (KR)
- Yonsei University (KR)
- Venue
- Journal of the Society for Social Work and Research
- Publisher
- University of Chicago Press
- Published
- 2025-03-01
- Volume
- 16
- Issue
- 1
- Pages
- 9-26
- ISSN
- 1948-822X (ISSN-L)
- 2334-2315
- OpenAlex
- W4407194683
- Cited by
- 32
- References
- 7
- Citations by year
- 2026: 27 · 2025: 5
- FWCI
- 52.48
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of the Society for Social Work and Research (publishedVersion)
- Topics
- Social Sciences › Public Administration › Social Work Education and Practice
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Social Sciences › General Social Sciences › Social Sciences and Policies
- Keywords
- AI literacy, socioeconomic disparities, marginalized communities, equity
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