Data Cleaning, Discard Studies, and Discretionary Power
Pınar Barlas · Proceedings of the AAAI/ACM Conference on AI Ethics and Society · 2025
Data cleaning is an overlooked yet impactful step in the Artificial Intelligence (AI) development pipeline, leading to negative downstream impacts when performed carelessly. Using Discard Studies as a framework, I propose an ethnographic study of how data practitioners exercise their discretionary power during the data cleaning process, particularly with respect to discarded data. The in-depth knowledge of the data cleaning process gained as a result of this study will allow us to improve guidelines and education on data cleaning for more ethical AI development.