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Closing the AI accountability gap: defining an end-to-end framework for internal algorithmic auditing.

, , , , , , , , and . FAT*, page 33-44. ACM, (2020)

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Using deep learning and Google Street View to estimate the demographic makeup of neighborhoods across the United States., , , , , , and . Proc. Natl. Acad. Sci. USA, 114 (50): 13108-13113 (2017)Scalable Annotation of Fine-Grained Categories Without Experts., , , and . CHI, page 1877-1881. ACM, (2017)Datasheets for Datasets, , , , , , and . (2018)cite arxiv:1803.09010Comment: Working Paper, comments are encouraged.Using Deep Learning and Google Street View to Estimate the Demographic Makeup of the US., , , , , , and . CoRR, (2017)Lessons from Archives: Strategies for Collecting Sociocultural Data in Machine Learning., and . CoRR, (2019)Closing the AI accountability gap: defining an end-to-end framework for internal algorithmic auditing., , , , , , , , and . FAT*, page 33-44. ACM, (2020)Diversity and Inclusion Metrics in Subset Selection., , , , , , , and . AIES, page 117-123. ACM, (2020)The TESCREAL bundle: Eugenics and the promise of utopia through artificial general intelligence., and . First Monday, (April 2024)Constructing a Visual Dataset to Study the Effects of Spatial Apartheid in South Africa., , , , and . NeurIPS Datasets and Benchmarks, (2021)Learning Features and Parts for Fine-Grained Recognition., , , , and . ICPR, page 26-33. IEEE Computer Society, (2014)