This document discusses using data science and digital technologies to better understand and influence human behavior change. It explores how collecting smartphone and user data can provide insights into behaviors like smoking cessation. Recommendation systems aim to tailor automated support to individuals, but challenges include a "cold start" period with little initial user data and ensuring interventions are grounded in behavioral theory rather than just predictive accuracy alone. Ongoing evaluation is also needed to test whether technologies truly enhance engagement and drive behavior change as intended.