NudgeRank: Digital Algorithmic Nudging for Personalized Health
<|reference_start|>NudgeRank: Digital Algorithmic Nudging for Personalized Health: In this paper we describe NudgeRank, an innovative digital algorithmic nudging system designed to foster positive health behaviors on a population-wide scale. Utilizing a novel combination of Graph Neural Networks augmented with an extensible Knowledge Graph, this Recommender System is operational in production, delivering personalized and context-aware nudges to over 1.1 million care recipients daily. This enterprise deployment marks one of the largest AI-driven health behavior change initiatives, accommodating diverse health conditions and wearable devices. Rigorous evaluation reveals statistically significant improvements in health outcomes, including a 6.17% increase in daily steps and 7.61% more exercise minutes. Moreover, user engagement and program enrollment surged, with a 13.1% open rate compared to baseline systems' 4%. Demonstrating scalability and reliability, NudgeRank operates efficiently on commodity compute resources while maintaining automation and observability standards essential for production systems.<|reference_end|>
@article{chiam2024nudgerank:,
    title={NudgeRank: Digital Algorithmic Nudging for Personalized Health},
    author={Jodi Chiam, Aloysius Lim, Ankur Teredesai},
    journal={arXiv preprint arXiv:2407.20241},
    year={2024},
    doi={10.1145/3637528.3671562},
    archivePrefix={arXiv},
    eprint={2407.20241},
    primaryClass={cs.CY cs.AI cs.LG}
}