Part 2: Ethical Decision-Making & Responsible AI Integration
ATTC Presents: Building on part one, this interactive session focuses on ethical frameworks and practical strategies for integrating AI into behavioral health practice responsibly. Participants will engage in case-based learning to evaluate AI outputs, identify risks, and apply ethical decision-making models grounded in behavioral health values. The session will also explore how behavioral health professionals can play a leadership role in co-designing AI tools with communities and supporting responsible implementation across systems.
OBJECTIVES:
By the end of this series, participants will be able to:
Define key concepts related to artificial intelligence, including large language models, machine learning, and decision-support tools, in the context of behavioral health practice.
Identify current and emerging applications of AI in social work and behavioral health settings, including both provider-facing and client-facing tools.
Recognize potential risks and harms, including algorithmic partiality, misinformation, privacy concerns, and preferential access to AI technologies.
Apply ethical frameworks grounded in behavioral health principles (e.g., dignity, autonomy, fairness) to evaluate the use of AI in real-world scenarios.
Critically assess AI-generated outputs for partiality, person-centered care, and trauma sensitivity.
Develop practical strategies for safely integrating AI into workflows while maintaining professional and ethical standards.
Define the role of behavioral health professionals as leaders in shaping, co-designing, and establishing the development of responsible AI systems in behavioral health.
Engage clients and communities in conversations about AI use, transparency, and consent in care delivery.
