Integrating Data Science Ethics Into an Undergraduate Major: A Case Study

• Published in: Journal of Statistics and Data Science Education Vol. 30; no. 1; pp. 15 - 28
• Main Authors: Baumer, Benjamin S., Garcia, Randi L., Kim, Albert Y., Kinnaird, Katherine M., Ott, Miles Q.
• Format: Journal Article
• Language: English
• Published: Alexandria Taylor & Francis 02.01.2022; Taylor & Francis Ltd; Taylor & Francis Group
• Subjects: Accountability; Algorithms; Artificial intelligence; Capstone Experiences; Capstone projects; Case Studies; College Faculty; College Science; Communities of Practice; Copyrights; Core curriculum; Course Descriptions; Curriculum Design; Data Analysis; Data ethics; Data science; Education; Ethics; Ethnicity; Introductory Courses; Liberal Arts; Machine learning; Majors (Students); Mathematical Models; Medicine; Music; Program Descriptions; Programming; R&D; Race; Research & development; Research ethics; School Policy; Science Curriculum; Science education; Science Instruction; Self Evaluation (Groups); Social Networks; Statistical Data; Statistics Education; Student Attitudes; Students; Teaching; Teaching Methods; Undergraduate curriculum; Undergraduate Students; Undergraduate Study; Massachusetts
• ISSN: 2693-9169; 2693-9169
• DOI: 10.1080/26939169.2022.2038041

We present a programmatic approach to incorporating ethics into an undergraduate major in statistical and data sciences. We discuss departmental-level initiatives designed to meet the National Academy of Sciences recommendation for integrating ethics into the curriculum from top-to-bottom as our majors progress from our introductory courses to our senior capstone course, as well as from side-to-side through co-curricular programming. We also provide six examples of data science ethics modules used in five different courses at our 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. We connect our efforts to a growing body of literature on the teaching of data science ethics, present assessments of our effectiveness, and conclude with next steps and final thoughts.