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Responsible Data Science - Fleming, Grant, and Bruce, Peter C
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Explore the most serious prevalent ethical issues in data science with this insightful new resource The increasing popularity of data science has resulted in numerous well-publicized cases of bias, injustice, and discrimination. The widespread deployment of "Black box" algorithms that are difficult or impossible to understand and explain, even for their developers, is a primary source of these unanticipated harms, making modern techniques and methods for manipulating large data sets seem sinister, even dangerous. When ...

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Responsible Data Science 2021, Wiley

ISBN-13: 9781119741756

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