4G: Data Ethics: Why, Where, and How?

Bryan D. Martin (University of Washington), Sarah Teichman (University of Washington), & Peter A. Gao (University of Washington)


Data and algorithmic ethics are becoming increasingly popular topics in statistical education. In this session, we will discuss three key questions that relate to incorporating ethics into an undergraduate statistics curriculum:

  • Why? We will begin with a short presentation based on our own experiences incorporating data ethics into an undergraduate curriculum. We will cover some of the discourse around the misuse of statistical methods, modern statistical methods for fairness, and why we believe it is important to teach students these topics.
  • Where? We will open up a discussion about where best to build ethics into a statistics curriculum. We hope that panelists will bring different perspectives about incorporating ethics as its own class, within existing classes, and other approaches.
  • How? We will break out into small groups to develop a data ethics activity for an undergraduate statistics classroom that builds on our previous presentation and discussion. Participants will work together to identify relevant topics and examples that illustrate ethical concerns in statistical practice and then draw connections to material in undergraduate statistics curricula.

There are three main goals of this session. First, we hope to help foster a community of statistics educators who are passionate about incorporating data ethics into their curricula. Second, we aim to have an interactive discussion about the logistics and strategies of incorporating data ethics into statistics curricula. Lastly, we hope that participants will leave the session with a concrete activity they can build into their own courses.