2025/01/26 by Sarah Ciston, Ciston, Sarah, Mike Ananny +3
Decision Sciences · #Big Data Technologies and Applications #Computers and Society (cs.CY) #FOS: Computer and information sciences
paper · pdf · doi:10.48550/arxiv.2501.15491
openalex publication_date 2025/01/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Machine learning datasets are powerful but unwieldy. Despite the fact that large datasets commonly contain problematic material--whether from a technical, legal, or ethical perspective--datasets are valuable resources when handled carefully and critically. A Critical Field Guide for Working with Machine Learning Datasets suggests practical guidance for conscientious dataset stewardship. It offers questions, suggestions, strategies, and resources for working with existing machine learning datasets at every phase of their lifecycle. It combines critical AI theories and applied data science concepts, explained in accessible language. Equipped with this understanding, students, journalists, artists, researchers, and developers can be more capable of avoiding the problems unique to datasets. They can also construct more reliable, robust solutions, or even explore new ways of thinking with machine learning datasets that are more critical and conscientious.