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Article
Understanding Machine Learning Practitioners' Data Documentation Perceptions, Needs, Challenges, and Desiderata
Amy K. Heger et al.
Proceedings of the ACM on Human-Computer Interaction (2022)
Review
Computer Science, Hardware & Architecture
Documentation to facilitate communication between dataset creators and consumers
Timnit Gebru et al.
Summary: Data plays a critical role in machine learning, with mismatched datasets potentially leading to negative model behaviors and societal biases amplification. The World Economic Forum suggests documenting the origin, creation, and use of machine learning datasets to prevent discriminatory outcomes.
COMMUNICATIONS OF THE ACM (2021)
Review
Computer Science, Artificial Intelligence
Data and its (dis)contents: A survey of dataset development and use in machine learning research
Amandalynne Paullada et al.
Summary: The work surveys literature that highlights limitations in dataset collection and usage practices in the field of machine learning, focusing on negative societal impacts and system performance. It covers approaches to mitigate bias in datasets and advocates for a combination of qualitative and quantitative methods for careful documentation and analysis during dataset creation and usage phases.
PATTERNS (2021)
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