October 11, 2024
The Department of Biostatistics is hosting this standalone half-day course on Ethical Reasoning for Statistics and Data Science. Attendance is free, and breakfast and parking are included. Register for the course through Eventbrite here. Registration has closed.
About the course
Ethical Reasoning for Statistics and Data Science
October 11, 9 a.m.–1 p.m.
Instructors:
Mario Davidson, PhD
The recent revision of the American Statistical Association Ethical Guidelines for Statistical Practice in combination with increased media attention on the ethics or data science algorithms has prompted our profession to renew its commitment to ethics education. We have developed DEPICT, a six-phase ethical reasoning process tailored to statistics and data science. In this course, we will present an overview of ethics paradigms and an overview of the American Statistical Association Ethical Guidelines followed by a deep dive into the DEPICT process. Students will define ethical dilemmas, explore possible resolutions, plan resolutions, anticipate issues associated with implementation, contemplate their actions, and transcend through understanding how key learnings can be incorporated into future approaches to similar situations. We will deliver the course in the context of multiple complex, nuanced case studies. Attendees will participate in small group discussions facilitated by the instructors as they apply the framework for the majority of the course. Students will be encouraged to develop multi-perspective views and debate the pros and cons of various resolutions based on professional guidance. In addition, they will report key elements of their small group discussion to the larger group.
This course is appropriate for students, faculty, early career professionals, seasoned thought leaders, and managers across government, industry, and academia. Individual contributors will learn how to apply the process to their own work. Leaders will learn how to leverage the process for group skills development in ethical reasoning. Faculty members will leave the course with materials and methods to incorporate into their statistics and data science courses. The course will consist of analyses of academic and industry/government cases. Participants who complete the pre-reading will get the most out of the group discussion and activities.
The course is free and will be held in person at 2525 West End Avenue in room 11105 (11th floor). A light continental breakfast and parking are included. We will send additional information to participants shortly before the course.
Mario Davidson is the associate vice chair of equity, diversity, and inclusion and an associate professor in the Department of Biostatistics at Vanderbilt University Medical Center.
Jennifer Van Mullekom is a professor of practice in the Department of Statistics and director of the Statistical Applications and Innovations Group (SAIG) at Virginia Tech.