The Human Element of Data Science: How to Teach Data Science Ethics

Applications of data science are increasingly being used in our daily lives, from helping decide who should be hired for a job to analyzing health data. With this expansion, ethical considerations have become an extremely important part of work in data science, especially in the context of decision-making. Despite this ethical imperative, ethics are often included as a last, token lecture in an introductory course or as an elective course for a data science major. This session will focus on how best to train future data scientists to see data as real people and consider ethical implications throughout their work. Open questions to be discussed include but are not limited to: what does it mean to be fair/ethical/transparent in data science, how/when should ethics be introduced to students, what should be covered in a lesson(s) on data science ethics, and how does teaching ethics in the context of data science differ from teaching ethics in other disciplines? The goal of this session is to promote productive discussion surrounding ethics training in data science that can lead to a standard ethical curriculum for data science courses.