Machine learning is the science of helping computers discover patterns and relationships in data. Two of the most common ways products use machine learning (ML) today are predictive recommendations and personalization. If you’ve checked out a recommended video on YouTube, then you’ve already experienced these features for yourself. And if you’re a UXer, perhaps you’re already incorporating ML into your own designs.At their best, ML-driven recommendations and personalized features save time and effort by proactively delivering the content users want without forcing them to navigate an interface or search. However, with the wrong execution, providing even the most accurate suggestion or the most relevant list of recommended items could actually require more time and effort from the user.To understand why this happens, and how to avoid this pitfall in your own designs, start by embracing a phenomenon known as habituation.