Social Work in the Age of Artificial Intelligence: A rights-Based Framework for evidence-Based Practice Through Social Psychology, Group Dynamics, and Institutional Analysis

Abstract

PURPOSE: This theoretical analysis aims to develop a comprehensive rights-based framework for navigating artificial intelligence integration in social work practice while addressing the ethical implications of AI deployment across micro, meso, and macro practice levels. MATERIALS AND METHODS: The study synthesized interdisciplinary research drawing on social psychology, group dynamics theory, and institutional analysis. The conceptual framework integrated the I-C-E (Ingroup Identification, Cohesion, Entitativity) model with socioecological systems theory. Analysis was conducted on existing literature and documented case examples to examine how AI systems mediate interpersonal relationships and construct meaning in social work contexts. RESULTS: The analysis demonstrated that AI systems profoundly impact vulnerable populations by mediating interpersonal relationships and constructing meaning in AI-mediated environments. The developed framework successfully bridged social work theory with interdisciplinary insights to provide evidence-based guidance for AI implementation in social services. DISCUSSION: The proposed framework offers concrete strategies for social work education and provides research methodologies that center community voices. The analysis reveals how AI integration can be guided by evidence-based practice while maintaining focus on vulnerable population needs and democratic governance principles in social services. CONCLUSION: This work provides evidence-based guidance for practitioners to harness AI's potential while safeguarding social work's core values of human dignity, self-determination, and social justice. The framework includes policy recommendations for democratic governance of AI in social services and establishes a foundation for ethical AI deployment across all levels of social work practice.

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