Ethics in Data Science (co-taught with Katie Shelef)

In this course, we will explore the moral, social, and ethical ramifications of the choices we make at the different stages of the data analysis pipeline, from data collection and storage to understand feedback loops in analysis. Through class discussions, case studies and exercises, students will learn the basics of ethical thinking in science, understand the history of ethical dilemmas in scientific work, and study the distinct challenges associated with ethics in modern data science.


Course Outline


Assignments will for the most part be essays that answer specific questions based on the assigned readings. Each assignment will generally be no more than 2 pages long (11 pt, single spaced) and should be turned in electronically (in PDF format, either generated directly or exported from another text editing mechanism).

Assignments will be graded based on your facility in


For your project, I'd like you to undertake a more detailed analysis of the ethical considerations in a data science setting of your choice. As an example of what you might want to aspire to (although you may not be able to achieve the level of detail in these articles), I present three case studies developed by the Council on Big Data, Ethics and Society.

These are merely ideas for how you might approach a particular scenario. But you should feel free to choose other topics/formats.

The Canvas page has a more detailed list of readings.