Counselors emphasize individualized treatment for diverse clients, but interventions are often guided by studies that assess average treatment effects. Causal machine learning provides a rigorous way to estimate who benefits most (or may be harmed) from specific interventions using clinical trial data, offering data-driven insights to achieve better individual outcomes. This session discusses the use of causal machine learning to support more precise, ethical, and client-centered practice.
