Abstract
This paper explores the integration of Artificial Intelligence (AI) into social work, mental health practice, and social work education, with a focus on Feedback-Informed Treatment (FIT) and its ethical implications. AI is increasingly being used in predictive analytics, mental health apps, and social work education through simulations, offering potential benefits like enhanced service delivery and access to mental health care. However, these technologies also introduce risks related to coercion, depersonalization, and ethical decision-making. The paper discusses the potential for AI to improve feedback mechanisms in both clinical practice and education, drawing on the FIT model, which emphasizes real-time, client-centered feedback. In educational settings, AI simulations provide immediate, tailored feedback to students, enhancing critical thinking and empathy, key competencies in social work. However, the use of AI also raises concerns about coercion and over-reliance on data-driven decision-making, which may conflict with social work values of client autonomy and empowerment. Ethical guidelines are essential to ensure that AI supports rather than undermines human-centered practices. Integrating AI with FIT principles could enhance both therapeutic outcomes and student learning while maintaining focus on human dignity and ethical responsibility.
Presenters
Tomi GomoryAssociate Professor, College of Social Work, Florida State University, Florida, United States
Details
Presentation Type
Paper Presentation in a Themed Session
Theme
KEYWORDS
Artificial Intelligence, Social Work, Feedback-Informed Treatment, Mental Health, Social Work Education, Coercion, Ethics Artificial Intelligence, Social Work, Feedback-Informed Treatment, Mental Health, Social Work Education, Coercion, Ethics
