Session: Using Empirical Evidence to Navigate the Frontiers of Artificial Intelligence in Human-Centered Fields: Implications for Social Work Research, Education, Practice, and Policy (Society for Social Work and Research 30th Annual Conference Anniversary)

Artificial intelligence (AI) has become increasingly embedded in education, legal decision-making, and human services. As a field rooted in ethical, social justice, and integrity, social work takes a crucial role in shaping how AI is implemented, not only within its own practice and pedagogy, but also across related human-centered disciplines. This interdisciplinary symposium brings together four studies that examine how social work and related fields, including psychology, education, and law, are responding to the integration of AI. The first presentation draws on focus group data with undergraduate and graduate students in social work and related disciplines to explore how they understand, critique, and engage with AI. Findings reveal a shared sense of ambivalence; that is, while students see AI's potential to improve efficiency and access to information, they express concerns about dehumanization, misinformation, and ecological impact, calling for an educational discourse on AI literacy that centers relational, ethical, and justice-oriented values. The second presentation uses thematic analysis to examine structural and institutional barriers to equitable AI education. It identifies how punitive academic policies, inconsistent guidance on AI use, regional and socioeconomic disparities, and generational divides hinder students' ability to engage meaningfully with AI tools. Simultaneously, students highlighted key facilitators, such as faculty mentorship, peer networks, and interdisciplinary exchange. By illuminating these systemic dynamics, the study calls for inclusive, contextually responsive strategies in social work education to ensure that all students, particularly those with limited technological access, are equipped to engage AI critically and ethically. The third presentation shifts focus to emerging social work professionals and explores how perceptions of knowledge and utility relate to AI engagement. Using survey data, the study finds that self-assessed knowledge and perceived usefulness significantly predict AI use, more so than prior exposure. These findings emphasize the importance of building not only technical familiarity, but also confidence and reflective awareness. The study recommends embedding both practical training and values-based discussion in social work curricula to foster ethical competence and purposeful application. The fourth presentation examines perspectives of legal professionals in the child welfare system. Findings show low current usage of AI, yet participants expressed clear expectations for accuracy, fairness, and transparency in any tools influencing decisions like family separation. These insights reveal cautious but conditional openness and highlight the need for collaborative frameworks that uphold procedural justice and social work ethics in interdisciplinary settings. Together, these presentations demonstrate how social work research can inform pedagogy, practice, and policy at a moment of profound technological change. By offering empirically grounded insights into AI literacy, curricular design, practice guidance, and systemic barriers, this symposium advances the conversation on how to prepare social workers to lead with integrity, care, and a commitment to social justice in the digital age.