Abstract
Data science projects continue to grow in number and importance. At the same time, the number of potential ethical conundrums that teams might encounter is also increasing. However, little has been done to investigate the perceived challenges and benefits of incorporating ethics oversight and analysis within a project. To address this gap, this paper reports on current practices, as well as the perceived benefits and challenges, with respect to how data scientists consider ethics analysis within a project. The results of the study show that most teams do not have an explicit process, and that potential ethical issues are identified in an ad hoc manner. The main challenges of incorporating ethics within a data science project were focused on the complexity and compatibility of being able to implement an ethics review process, while the benefits focused on the relative ad-vantage of an improved analysis and the fact that others will know that the project has considered it’s ethical implications. While more work is required to validate and refine these findings, this analysis can help teams as they consider integrating ethics analysis within their data science project.
Recommended Citation
saltz, jeff, (2019). "ETHICS IN DATA SCIENCE PROJECTS: CURRENT PRACTICES AND PERCEPTIONS". In Proceedings of the 27th European Conference on Information Systems (ECIS), Stockholm & Uppsala, Sweden, June 8-14, 2019. ISBN 978-1-7336325-0-8 Research-in-Progress Papers.
https://aisel.aisnet.org/ecis2019_rip/68