Designing Trustworthy ML Models: Alan & Aida Discover Monotonicity in Machine Learning

Machine learning models require more than just accuracy to be trustworthy; they must also align with common sense and business rules. Monotonicity constraints ensure that predictions move in a consistent direction as an input feature changes, such as house prices never decreasing as square footage increases. Using a narrative about house price prediction, the content demonstrates how to identify and fix monotonicity violations. This can be implemented in libraries like XGBoost to create more interpretable, logical, and reliable models that better align with regulatory expectations and business logic.