#45 Decision Intelligence and Data Science

In this episode of DataFramed, Hugo Bowne-Anderson interviews Cassie Kozyrkov, Chief Decision Scientist at Google Cloud, about data science, decision making, and decision intelligence. Cassie defines data science as a discipline of decision making, incorporating statistical inference, machine learning, and analytics. She emphasizes the importance of applied data science in solving real-world business problems and avoiding type 3 errors, which is solving the wrong problem correctly. They discuss organizational models for embedding data scientists, such as centralized teams, embedded engineers, decision support roles, and decision intelligence operatives, each with its pros and cons. Cassie stresses the need for data literacy, humility, and interdisciplinary collaboration to effectively turn information into action and make data useful, advocating for a shift from pure research to applied data science to leverage the increasing volume of available data for beneficial outcomes.