Decoding AI's Impact on Treatment Effect Estimates: Can We Trust the Numbers?
Explore how machine learning, particularly double machine learning (DML), is transforming the estimation of treatment effects, and the innovative techniques being developed to address challenges like unbalanced data. Learn about the calibrated-undersampled DML (CU-DML) estimator and its potential to enhance the reliability of AI-driven insights in healthcare, economics, and beyond.