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Building products that use machine learning or artificial intelligence comes with significant challenges. AI-driven products are not deterministic – they make mistakes, and they behave differently in seemingly similar situations, which is something users are not typically comfortable with. They might also make recommendations that a user disagrees with or didn't expect. Not only is this a risk for the user – they might choose to ignore all the AI features as a result – but it could lead to experiences that make the user decide against using the product again. In this article, we explore three major types of ML-driven products and provide five design considerations for ML product managers.