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Artificial Intelligence DIsContinuation Effects (AI-DICE): An Emerging Phenomenon in Mental Health Applications
ABSTRACT
Artificial intelligence (AI) has emerged as a powerful tool for fostering positive behavior change and enhancing mental health support. However, the abrupt discontinuation of AI-driven interventions, particularly those featuring conversational agents, may trigger unintended psychological consequences. Therefore, we introduce and examine the concept of Artificial Intelligence DIsContinuation Effects (DICE), drawing compelling parallels from abandonment-like experiences observed from problematic termination experiences with therapists. A conceptual framework for AI-DICE mitigation is proposed, emphasizing insights from user experience research and foundational principles of behavior change, such as structured goal setting. Concepts from Acceptance and Commitment Therapy provide a framework for AI-DICE mitigation and are especially relevant for interventions focused on substance use. Integrating perspectives from community-engaged research will increase trust. AI-DICE raises important ethical challenges, including transparency, the ability to withdraw or adapt participation as the users’ knowledge of the intervention grows, and access to support post-intervention. Prioritizing long-term continuation, or at least some form of ongoing access, over the best-planned complete discontinuation strategy may help ensure that AI-driven mental health solutions deliver lasting benefits rather than unintended harm.
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