From extrinsic to intrinsic motivation: Testing an AI-powered motivational interviewing system to foster prosocial motivation

Scalable interventions promoting sustained behavioral change are crucial for addressing societal issues, yet traditional approaches often require intensive one-on-one therapy. We developed and tested Intrinsic AI, a motivational interviewing chatbot built on GPT-4 and tuned using self-determination theory principles, to increase prosocial behavior. In a preregistered randomized controlled trial (N=237), participants either engaged in a 15-minute conversation with Intrinsic AI about becoming more prosocial or talked freely with an unmodified version of GPT-4. We measured changes in motivation using validated self-report scales and assessed prosocial behavior through an effort-based decision-making task where participants chose between exerting cognitive effort for themselves versus charity. Compared to controls, participants who interacted with Intrinsic AI showed greater increases in motivational readiness as assessed by the motivational interviewing ruler, reporting that becoming prosocial was more important to them, that they felt more confident in their ability to change, and that they were more ready to begin. However, this motivational gain did not persist at 24-hour follow-up, translate into trait level changes in motivation, or influence prosocial effort in a behavioral task. Our findings demonstrate that theoretically grounded AI chatbots can effectively increase short-term prosocial motivation and suggest that a single brief interaction may be insufficient for creating lasting motivational change or impact actual prosocial behavior. This work provides a proof-of-concept for automated motivational interviewing while highlighting the need for more sustained AI-human interactions to achieve durable behavioral change. • Developed chatbot based on GPT-4 using motivational interviewing principles • Intrinsic AI increased short-term prosocial motivation in a randomized trial • Gains in importance, confidence, and readiness were not sustained after 24h • No impact on trait motivation or actual prosocial behavior was observed • Demonstrates potential for scalable AI-based motivational interventions

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Publication Details

Journal
Computers in Human Behavior Reports
Published
2025-11-20
DOI
https://doi.org/10.1016/j.chbr.2025.100882
Primary Topic
Digital Mental Health Interventions
Type
article
Field-Weighted Citation Impact
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article

From extrinsic to intrinsic motivation: Testing an AI-powered motivational interviewing system to foster prosocial motivation

Michael Inzlicht, Conrado Eiroa-Solans
Computers in Human Behavior Reports
Digital Mental Health Interventions
article

From extrinsic to intrinsic motivation: Testing an AI-powered motivational interviewing system to foster prosocial motivation

Michael Inzlicht, Conrado Eiroa-Solans
article en

Abstract

Scalable interventions promoting sustained behavioral change are crucial for addressing societal issues, yet traditional approaches often require intensive one-on-one therapy. We developed and tested Intrinsic AI, a motivational interviewing chatbot built on GPT-4 and tuned using self-determination theory principles, to increase prosocial behavior. In a preregistered randomized controlled trial (N=237), participants either engaged in a 15-minute conversation with Intrinsic AI about becoming more prosocial or talked freely with an unmodified version of GPT-4. We measured changes in motivation using validated self-report scales and assessed prosocial behavior through an effort-based decision-making task where participants chose between exerting cognitive effort for themselves versus charity. Compared to controls, participants who interacted with Intrinsic AI showed greater increases in motivational readiness as assessed by the motivational interviewing ruler, reporting that becoming prosocial was more important to them, that they felt more confident in their ability to change, and that they were more ready to begin. However, this motivational gain did not persist at 24-hour follow-up, translate into trait level changes in motivation, or influence prosocial effort in a behavioral task. Our findings demonstrate that theoretically grounded AI chatbots can effectively increase short-term prosocial motivation and suggest that a single brief interaction may be insufficient for creating lasting motivational change or impact actual prosocial behavior. This work provides a proof-of-concept for automated motivational interviewing while highlighting the need for more sustained AI-human interactions to achieve durable behavioral change. • Developed chatbot based on GPT-4 using motivational interviewing principles • Intrinsic AI increased short-term prosocial motivation in a randomized trial • Gains in importance, confidence, and readiness were not sustained after 24h • No impact on trait motivation or actual prosocial behavior was observed • Demonstrates potential for scalable AI-based motivational interventions

Computers in Human Behavior ReportsVol. 21
University of Toronto (CA), University of California, Berkeley (US)
Openalex Percentile: Top 61%
Digital Mental Health Interventions
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