Datasheets for Datasets
원문 초록
The machine learning community currently has no standardized process for documenting datasets, which can lead to severe consequences in high-stakes domains. To address this gap, we propose datasheets for datasets. In the electronics industry, every component, no matter how simple or complex, is accompanied with a datasheet that describes its operating characteristics, test results, recommended uses, and other information. By analogy, we propose that every dataset be accompanied with a datasheet that documents its motivation, composition, collection process, recommended uses, and so on. Datasheets for datasets will facilitate better communication between dataset creators and dataset consumers, and encourage the machine learning community to prioritize transparency and accountability.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
AnalogVNN: A fully modular framework for modeling and optimizing photonic neural networks
Evolutionary bagging for ensemble learning
Neural network accelerator for quantum control
Deep Reinforcement Learning for Multi-Agent Interaction
Disparate Censorship & Undertesting: A Source of Label Bias in Clinical Machine Learning
Unsupervised machine learning framework for discriminating major variants of concern during COVID-19
토론
이 논문과 연결된 포럼 글이 아직 없습니다.