Asia Pacific Journal of Social Work & Development

The Professional and Ethical Use of AI in Social Work

Key Questions for the Special Issue

Contributors may wish to consider questions such as:

•    How is AI currently being used in social work and human service organizations?
•    What opportunities does AI offer for improving social work practice and service delivery?
•    What risks does AI pose to equity, justice, and human rights?
•    How can social workers critically evaluate and responsibly use AI tools?
•    What ethical frameworks are needed to guide AI use in social work?
•    How should social work education prepare students and practitioners for AI-informed practice?
•    How can communities, service users, and marginalized groups be included in decisions about AI design and implementation?

Scope and Topics of Interest

We welcome manuscripts addressing, but not limited to, the following themes:

1.    AI in Social Work Practice: Assessment, Intervention, and Service Planning

•    Predictive analytics and risk assessment
•    AI and the social worker–service user relationship
•    Impacts of AI on therapeutic alliance, trust, empathy, and relational practice
•    Service user autonomy, informed consent, and participation in AI-supported practice
•    Integration of AI tools into case management workflows and organizational routines
•    The role of AI in resource allocation and service prioritization
•    The potential for AI to reduce systemic inequalities
•    Practitioner experiences and/or resistance in AI-mediated practice

2.    AI in Social Work Education: Pedagogy, Literacy, and Competency Development

•    Generative AI in social work teaching, learning, and assessment
•    AI-supported reflective learning and supervision
•    Simulated client interactions, virtual role plays, and scenario-based learning
•    Digital literacy and AI literacy as core social work competencies
•    Curriculum design for preparing AI-informed and critically engaged practitioners
•    Ethical dilemmas arising from student use of AI in assignments and fieldwork
•    Field education policies related to AI tools and digital platforms
•    Faculty readiness of pedagogical innovation in social work education

3.    AI in Social Work Research: Methods, Data, and Knowledge Production

•    Use of large language models for data analysis, literature review, coding, or synthesis
•    AI-assisted analysis of administrative, clinical, organizational, or community data
•    Predictive modeling and pattern detection in social welfare research
•    Participatory AI and community-engaged approaches to AI research
•    Reproducibility, transparency, and validation of AI-assisted research methods
•    Machine learning and computational social science methods in social work research

4.    Ethical and Responsible AI: Governance, Bias, and Accountability

•    Ethical tensions in AI-supported social work practice
•    Algorithmic bias, discrimination, and structural inequality
•    Transparency, explainability, and contestability of AI decisions
•    Professional liability when AI informs, recommends, or overrides decisions
•    Ethical responsibilities of practitioners, agencies, and policymakers
•    Comparative analysis of professional ethics codes and AI governance frameworks
•    Rights-based, anti-oppressive, and justice-oriented approaches to AI governance

5.    Philosophical and Critical Perspectives on AI in Social Work

•    Ontological and epistemological questions raised by AI in social work
•    Posthumanist, critical realist, phenomenological, and decolonial perspectives on AI
•    Human agency, autonomy, dignity, and vulnerability in AI-mediated practice
•    Care ethics, relational ethics, and anti-oppressive theory as frameworks for AI critique
•    Critiques of techno-solutionism, automation, and datafication in social work
•    Epistemic injustice, algorithmic authority, and marginalized ways of knowing
•    Alternative theoretical frameworks for socially just and relationally grounded AI
•    The role of social work in resisting harmful technologies and imagining emancipatory digital futures