Metro21 Lunch and Learn: Public Policy Analytics: Code and Context for Data Science in Government Postponed until a later date. Join Metro21 as we hear Dr. Ken Steif discuss his project, "Public Policy Analytics: Code & Context for Data Science in Government." How do algorithms in government differ from business? In business, revenue is the only relevant bottom line, but in government algorithms must optimize for several disparate bottom lines like equity, fairness, bureaucracy, politics and more. In his new book, 'Public Policy Analytics: Code & Context for Data Science in Government', Dr. Ken Steif presents both code examples and an analytical framework for developing algorithms to meet these requirements. In this talk, he will discuss why data science and Planning are one in the same; how certain machine learning algorithms can help governments better allocate their limited resources; and how 'Algorithmic Governance' can help agencies develop data science tools that are both useful and fair. Take a look at the open source version of the book here.