Session: AI for Health & Social Equity: Student Innovations in Social Work Research (Society for Social Work and Research 30th Annual Conference Anniversary)

Artificial intelligence (AI) is increasingly shaping the landscape of health and social work, offering novel approaches to address misinformation, policy inequities, and mental health disparities. This symposium showcases three innovative student-led research projects leveraging AI to advance health and social equity and conducted at the New York University Silver School of Social Work in collaboration with the C+M Center on Data Science and Social Equity. NYU Silver and the C+M Center are helping to lead the field in supporting, supervising, and promoting student research at the intersection of AI and social equity. These student projects illustrate the transformative potential of AI in enhancing public health communication, assessing the impact of legislation on vulnerable populations, and analyzing mental health discourse in marginalized communities.

The first study introduces a retrieval-augmented large language model (LLM) designed to improve the accuracy of COVID-19 fact-checking. By integrating a retrieval-augmented generation (RAG) system, the model significantly reduces misinformation by grounding responses in peer-reviewed literature. The findings highlight AI's capacity to enhance public health interventions and identify misinformation during crises.

The second study examines the effects of state-level legislation on suicidality among sexual minority youth. By integrating AI-driven data analysis of the Youth Risk Behavior Survey and legislative records, the research identifies the protective role of inclusive policies and the detrimental effects of discriminatory laws. The study underscores the importance of AI-enhanced policy analysis in advocating for data-driven legislative change to support LGBTQ+ youth.

The final study utilizes AI-based topic modeling and emotion recognition to analyze mental health discourse within Black online communities. By applying neural network-based natural language processing to Reddit posts, the research uncovers key themes and affective patterns in discussions about identity, relationships, and systemic stressors. The findings highlight how AI can be used to identify and address mental health disparities in marginalized communities.

Collectively, these student projects illustrate AI's growing role in social work research and training for social work scholars. They demonstrate the potential for AI to enhance data analysis, inform policy, and uncover community-specific health challenges. The symposium will include remarks from Dean and Paulette Goddard Professor of Social Work at NYU Silver, Dr. Michael Lindsey, on training next-generation social work scholars in AI and data science. The symposium will conclude with a discussion exploring the ethical considerations of AI-driven research and strategies to ensure AI is leveraged for equitable and inclusive social work research and practice.