Ethics and Policy in Data Science

Data-informed decision making has created new opportunities, e.g. personalized marketing and recommendations, but also expands the set of possible risks, e.g. privacy, security, etc.; this is especially true for businesses collecting, storing, and analyzing human data. Organizations need to consider the "should we?" question with regard to data and analytics, and not just be concerned with “can we?”.  In this course, we will explore ethical frameworks, guidelines, codes, and checklists, and also consider how they apply to all phases of the data science process. Existing research ethics standards provide a necessary but insufficient foundation when doing data science and analytics. Together, we will wrestle with the rapidly-changing capabilities, conflicts, and desires that emerge from new data practices. Upon completion of the course, you will be able to identify and balance: what an organization wants to do from a business perspective, can do from technical and legal perspectives, and should do from an ethical perspective.