Search Results for author: Sarah Newman

Found 2 papers, 1 papers with code

The Dataset Nutrition Label (2nd Gen): Leveraging Context to Mitigate Harms in Artificial Intelligence

no code implementations10 Jan 2022 Kasia S. Chmielinski, Sarah Newman, Matt Taylor, Josh Joseph, Kemi Thomas, Jessica Yurkofsky, Yue Chelsea Qiu

This paper discusses the harm and bias from underlying training data that the Label is intended to mitigate, the current state of the work including new datasets being labeled, new and existing challenges, and further directions of the work, as well as Figures previewing the new label.

Decision Making Nutrition

The Dataset Nutrition Label: A Framework To Drive Higher Data Quality Standards

1 code implementation9 May 2018 Sarah Holland, Ahmed Hosny, Sarah Newman, Joshua Joseph, Kasia Chmielinski

The Dataset Nutrition Label (the Label) is a diagnostic framework that lowers the barrier to standardized data analysis by providing a distilled yet comprehensive overview of dataset "ingredients" before AI model development.

Databases Computers and Society

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