Time2Stop: Adaptive and Explainable Human-AI Loop for Smartphone Overuse Intervention
arxiv(2024)
摘要
Despite a rich history of investigating smartphone overuse intervention
techniques, AI-based just-in-time adaptive intervention (JITAI) methods for
overuse reduction are lacking. We develop Time2Stop, an intelligent, adaptive,
and explainable JITAI system that leverages machine learning to identify
optimal intervention timings, introduces interventions with transparent AI
explanations, and collects user feedback to establish a human-AI loop and adapt
the intervention model over time. We conducted an 8-week field experiment
(N=71) to evaluate the effectiveness of both the adaptation and explanation
aspects of Time2Stop. Our results indicate that our adaptive models
significantly outperform the baseline methods on intervention accuracy (>32.8%
relatively) and receptivity (>8.0%). In addition, incorporating explanations
further enhances the effectiveness by 53.8% and 11.4% on accuracy and
receptivity, respectively. Moreover, Time2Stop significantly reduces overuse,
decreasing app visit frequency by 7.0∼8.9%. Our subjective data also
echoed these quantitative measures. Participants preferred the adaptive
interventions and rated the system highly on intervention time accuracy,
effectiveness, and level of trust. We envision our work can inspire future
research on JITAI systems with a human-AI loop to evolve with users.
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