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The Future of Registered Behavior Technicians (RBT) Support: Exploring Artificial Intelligence (AI) Co-Pilots in Applied Behavior Analysis (ABA) Service Delivery |
Sunday, May 25, 2025 |
11:00 AM–11:50 AM |
Convention Center, Street Level, 146 B |
Area: OBM/EDC; Domain: Applied Research |
CE Instructor: Rick M. Kubina, Ph.D. |
Chair: Rick M. Kubina (Penn State) |
KELLY KING (CentralReach) |
BOBBY NEWMAN (Proud Moments) |
RICK M. KUBINA (Penn State) |
Abstract: The field of applied behavior analysis faces ongoing challenges with RBT retention and support, impacting both service quality and organizational sustainability. This panel brings together experts from clinical practice, technology development, and workforce research to examine the potential role of artificial intelligence in supporting newly hired RBTs. Panelists will discuss recent pilot studies of AI co-pilot implementations, methodological considerations for evaluating such technologies, ethical implications for the field, and practical challenges in implementation. The discussion will focus on key questions including: How might AI support systems impact RBT retention and job satisfaction? What are the benefits and limitations of current AI co-pilot technologies in behavioral healthcare? How can organizations effectively evaluate and implement these tools while maintaining high clinical standards? This panel aims to facilitate an evidence-based discussion of technology's evolving role in clinical support systems while examining important considerations for the future of the field. Audience participation will be encouraged to explore diverse perspectives on this emerging practice area. |
Instruction Level: Basic |
Target Audience: New and advanced behavior technicians (BTs and RBTs), behavior analysts (BCBAs and BCBA-Ds), and administrators (clinical directors) |
Learning Objectives: 1. Compare and contrast at least three potential benefits and three limitations of using AI co-pilot systems for RBT support based on current implementation data 2. Identify five key ethical considerations when implementing AI technology in clinical supervision and RBT support 3. Evaluate the effectiveness of AI support systems using at least three measurable metrics related to staff retention and clinical outcomes |
Keyword(s): Artificial intelligence, Clinical supervision, Technology integration, Workforce retention |
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