| Abstract: The Advancement of technology has provided more options to support the application of behavior-analytic techniques. This presentation explores the integration of artificial intelligence (AI) into behavior analytic service delivery, focusing on its application in training behavior technicians. Cox and Jenning (2024) underscored the potential benefits AI for customizing services to address the unique needs of clients, increased efficiency in administrative tasks, enhanced decision-making through the synthesis of relevant research, and improved client outcomes through optimized resource allocation. The literature has demonstrated the potential of AI to enhance training within the behavior analytic field (Clark, 2020; Griffen et al., 2024; Huang et al., 2021). In last year’s convention, the presenter shared the results of AI-based training to improve compassionate care skills of BCBAs. This presentation is the extension of the previous study in which the AI-based training will be implemented for behavior technicians. The presentation will discuss innovative AI-driven training methodologies designed to improve the competency of behavior technicians in completing session notes with precision and consistency. Preliminary data from the ongoing study will be presented, providing insights into the effectiveness of AI-enhanced training for behavior technicians. Additionally, the presentation will explore the broader implications of incorporating AI in this capacity, including potential scalability, adoption in clinical settings, and avenues for future research and development. Clark, D. (2020). Artificial intelligence for learning: How to use AI to support employee development. Kogan Page Publishers. Cox, D. J., & Jennings, A. M. (2024). The promises and possibilities of artificial intelligence in the delivery of behavior analytic services. Behavior Analysis in Practice, 17(1), 123-136. Griffen, B., Lorah, E. R., Caldwell, N., Hantula, D. A., Nosek, J., Tincani, M., & Lemley, S. (2024). The effects of artificial intelligence on implementors’ fidelity of instructional strategies during handwashing acquisition in children with autism. Journal of Developmental and Physical Disabilities, 36(5), 793-819. Huang, J., Saleh, S., & Liu, Y. (2021). A review on artificial intelligence in education. Academic Journal of Interdisciplinary Studies, 10(3). |
| Abstract: Job interviews are intimidating to most job seekers, but for autistic job seekers, the interview process can be especially challenging due to difficulties they may face with social interaction and communication. Some of these difficulties may be addressed with coaching and training, however this approach is limited as coaching and training are resource-intensive and do not scale. An artificial intelligence (AI) based solution does not suffer these limitations and may also be adapted to the individual needs and preferences of the job seeker. To learn how job seekers and job coaches view such an AI tool, we conducted an exploratory study to learn more about these employment interview challenges, conducting structured interviews with five autistic job seekers and five vocational coaches. During the structured interviews, participants interacted with a prototype of an intelligent employment interview coach chatbot to share their perspectives about using a chatbot to prepare for behavioral interview questions. From the themes uncovered in our structured interviews, we provide insight into the unique challenges that autistic job seekers face while interviewing, and the interview preparation support given by vocational coaches. We discuss the potential of an intelligent interview coach chatbot to assist autistic job seekers during the interview preparation process, and also share suggestions for future design considerations of intelligent interview coaches as collaborative assistants for autistic job seekers and vocational coaches. An AI based employment interview coach is well accepted by both the job seekers and job coaches. |