• Teaching

    INFO 4270: Ethics and Policy in Data Science, Cornell University, Fall 2017

    This class will teach you to recognize where and understand why ethical issues and policy questions can arise when applying data science to real world problems. It will bring analytic and technical precision to normative debates about the role that data science, machine learning, and artificial intelligence play in consequential decision-making in commerce, employment, finance, healthcare, education, policing, and other areas. We will focus on ways to conceptualize, measure, and mitigate bias in data-driven decision-making, to audit and evaluate models, and to render these analytic tools more interpretable and their determinations more explainable. You will learn to think critically about how to plan, execute, and evaluate a project with these concerns in mind, and how to cope with novel challenges for which there are often no easy answers or established solutions.

    To do so, you will develop fluency in the key technical, ethical, policy, and legal terms and concepts that are relevant to a normative assessment of data science; learn about some of the common approaches and emerging tools for mitigating or managing these ethical concerns; and gain exposure to legal scholarship and policy documents that will help you understand the current regulatory environment and anticipate future developments. Ultimately, the class will teach you how to reason through these problems in a systematic manner and how to justify and defend your approach to dealing with them.

     

    INFO 6210: Information, Technology, and Society, Spring 2017