Conference Papers  |    |  February 21, 2018

Key Concepts for a Data Science Ethics Curriculum

Conference paper by Jeffrey S. Saltz, Neil I. Dewar and Robert Heckman.
Presented at SIGCSE ’18, the 49th ACM Technical Symposium on Computer Science Education.


Data science is a new field that integrates aspects of computer science, statistics and information management. As a new field, ethical issues a data scientist may encounter have received little attention to date, and ethics training within a data science curriculum has received even less attention. To address this gap, this article explores the different codes of conduct and ethics frameworks related to data science. We compare this analysis with the results of a systematic literature review focusing on ethics in data science. Our analysis identified twelve key ethics areas that should be included within a data science ethics curriculum. Our research notes that none of the existing codes or frameworks covers all of the identified themes. Data science educators and program coordinators can use our results as a way to identify key ethical concepts that can be introduced within a data science program.