This talk is about how we can utilize design thinking to help better define data science problems upfront and help reduce requirements churn. It makes a business case for UX feedback in many stages of the Data Science life cycle and aims to bring an awareness of UX as a discipline in the context of Data Science and AI.It intends to bring a point of view that is a bit outside (but still complementary) of a data scientist’s typical ways of thinking about DS work.It also explores ways in which AI can help UX.

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