> ML_LITERATURE // GEBRU-2021-DATASHEETS-FOR-DATASETS_v1.0
Datasheets for Datasets
Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daumé III, Kate Crawford · Communications of the ACM (CACM) (2021)
standard-technical-report2021industry-standardartifactsAvailable
Principal Contribution
Proposed standardizing documentation for machine learning datasets inspired by hardware electronics datasheets, detailing motivation, composition, collection, and ethical considerations.
Operational Relevance
Serves as qualified reference for implementing task-data-validation in production systems.
Assumptions
- Underlying computational topology and mathematical bounds adhere to established convexity/smoothness guarantees
Limitations
- Hardware runtime speedups, privacy budgets, and convergence depend on hyperparameters and network communication limits
Connected Algorithms, Architectures & Tools
Related Algorithms:
Related Architectures:
Implementing Libraries: