A new catalog classifying 35 data error types into missing, incorrect, and redundant categories for tabular data, with definitions and examples to improve data quality management.
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The paper argues that preoccupation with the moral status of hypothetical future AI creates an algorithmic blind spot that marginalizes existing algorithmic harms to human populations and calls for re-centering ethics on current institutional accountability.
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A Catalog of Data Errors
A new catalog classifying 35 data error types into missing, incorrect, and redundant categories for tabular data, with definitions and examples to improve data quality management.
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The Algorithmic Blind Spot: Bias, Moral Status, and the Future of Robot Rights
The paper argues that preoccupation with the moral status of hypothetical future AI creates an algorithmic blind spot that marginalizes existing algorithmic harms to human populations and calls for re-centering ethics on current institutional accountability.