Abstract
Artificial intelligence (AI) has begun to affect nearly every aspect of our daily lives and nearly every industry and profession. Many readers of this journal likely work in one or more areas of behavioral health. For readers who work in behavioral health and who are interested in AI, the purpose of this article is to highlight the pervasiveness of AI research being conducted around many facets of behavioral health service delivery. To do this, we first provide a brief overview of some of the areas within AI and the types of problems each area of AI attempts to solve. We then outline the prototypical client journey in behavioral healthcare beginning with diagnosis/assessment and ending with intervention withdrawal or ongoing monitoring. Next, for each stage in the client journey, we highlight several areas that parallel existing behavior analytic practice where researchers have begun to use AI, often to improve the efficiency of service delivery or to learn new things that improve the effectiveness of behavioral health services. Finally, for those whose appetite has been whet for getting involved with AI, we close by describing three roles they might consider trying out and that parallel the three main domains of behavior analysis. These three roles are an AI tool designer (akin to EAB), AI tool implementer (akin to ABA), or AI tool supporter (akin to practice).
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No datasets were generated or analyzed during the current study.
Notes
Like behavior analysis, artificial intelligence (AI) is comprised of a broad set of behaviors implemented by many different people and toward many different applications. Thus, no section in a single article is likely to fully encompass all methods, approaches, applications, and technical specifications required to fully define AI; especially considering that the definition of what counts as “intelligent” is currently debated. Compounding this complexity is that building and deploying AI systems is often highly interdisciplinary further making it difficult to comprehensively define the totality of what “counts as AI.” Readers interested in diving more into the technical details are encouraged to read Müller and Guido (2016), Everitt et al. (2011), Goodfellow et al. (2016), and Sutton and Barto (1998).
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Cox, D.J., Jennings, A.M. The Promises and Possibilities of Artificial Intelligence in the Delivery of Behavior Analytic Services. Behav Analysis Practice 17, 123–136 (2024). https://doi.org/10.1007/s40617-023-00864-3
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DOI: https://doi.org/10.1007/s40617-023-00864-3