This month, in the CAUSE (Consortium for the Advancement of Undergraduate Statistics Education) / JSDSE (Journal of Statistics and Data Science Education) webinar series, we highlight the research article, Integrating Data Science Ethics Into an Undergraduate Major. In the webinar, the presenters will present a programmatic approach to incorporating ethics into an undergraduate major in statistical and data sciences. They will discuss departmental-level initiatives designed to meet the National Academy of Sciences recommendation for integrating ethics into the curriculum from top-to-bottom as their majors progress from the introductory courses to the senior capstone course, as well as from side-to-side through co-curricular programming. They will also provide six examples of data science ethics modules used in five different courses at their liberal arts college, each focusing on a different ethical consideration. The modules are designed to be portable such that they can be flexibly incorporated into existing courses at different levels of instruction with minimal disruption to syllabi. The presenters will connect their efforts to a growing body of literature on the teaching of data science ethics, present assessments of their effectiveness, and conclude with next steps and final thoughts.
Presented By: Benjamin S. Baumer (Smith College) and Katherine M. Kinnaird (Smith College)
Benjamin S. Baumer is an associate professor in the Statistical & Data Sciences program at Smith College. Ben is a co-author of The Sabermetric Revolution, Modern Data Science with R, and the second edition of Analyzing Baseball Data with R. Ben has received the Waller Education Award from the ASA Section on Statistics and Data Science Education, the Significant Contributor Award from the ASA Section on Statistics in Sports, and the Contemporary Baseball Analysis Award from the Society for American Baseball Research. His research interests include sports analytics, data science, statistics and data science education, statistical computing, and network science.
Katherine M. Kinnaird is the Clare Boothe Luce Assistant Professor of Computer Science and Statistical & Data Sciences at Smith College. She is a computational researcher working at the intersection of machine learning, mathematics and cultural analytics. Kinnaird has been involved with the Workshop for Women in Machine Learning (WIML), the American Mathematical Society's Committee on Education, and the Women in Music Information Retrieval (WiMIR) Workshop.
The webinar will take place on July 19th, from 1:30-2:00 pm EDT. Please note the earlier time .
Registration is required but is free:
We hope that you can join us for an informative discussion.
Leigh Johnson (Capital University)
Moderator, CAUSE/JSDSE Webinar Series