From predictive medicine to autonomous driving, advances in Artificial Intelligence (AI) promise to improve people’s lives and improve society. As systems that utilize these advances increasingly migrated from research labs into the real world, new challenges emerged. For example, when and how should predictive models fit into physicians’ decision-making workflow such that the predictions impact them appropriately? These are challenges of translation: translating AI systems from systems that demonstrate remarkable technological achievements into real-world, socio-technical systems that serve human ends. My research focuses on this critical translation; on the user experience (UX) design of AI systems. The prevalence of AI suggests that the UX design community has effective design methods and tools to excel in this translation. While this is true in many cases, some challenges persist. For example, designers struggle with accounting for AI systems’ unpredictable errors, and these errors damage UX and even lead to undesirable societal impacts