Introduction
In this course, students will explore the ethical complexities of information and communication technology, as well as of data science in general. Combining theoretical foundations from information ethics and real-world inquiry, students will build their ethical imaginations and skills for ethically collecting, storing, sharing and analyzing data derived from human subjects including data used in algorithms. To this end, the course will examine legal, policy, and ethical issues that arise throughout the full lifecycle of data science from collection, to storage, processing, analysis and use, including, privacy, surveillance, security, classification, discrimination, decisional-autonomy, and duties to warn or act. Practically, using case studies, students will explore current applications of quantitative reasoning in organizations, algorithmic transparency, and unintended automation of discrimination via data that contains biases rooted in race, gender, class, and other characteristics.