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Standards for the Control of Algorithmic Bias - Hardcover

 
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  • PublisherCRC Press
  • Publication date2023
  • ISBN 10 1032550228
  • ISBN 13 9781032550220
  • BindingHardcover
  • LanguageEnglish
  • Edition number1
  • Number of pages108

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Heisler, Natalie,Grossman, Maura R.
Published by CRC Press, 2023
ISBN 10: 1032550228 ISBN 13: 9781032550220
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Heisler, Natalie; Grossman, Maura
Published by CRC Press, 2023
ISBN 10: 1032550228 ISBN 13: 9781032550220
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Natalie Heisler
Published by Taylor & Francis Ltd, London, 2023
ISBN 10: 1032550228 ISBN 13: 9781032550220
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Hardcover. Condition: new. Hardcover. Governments around the world use machine learning in automated decision-making systems for a broad range of functions. However, algorithmic bias in machine learning can result in automated decisions that produce disparate impact and may compromise Charter guarantees of substantive equality. This book seeks to answer the question: what standards should be applied to machine learning to mitigate disparate impact in government use of automated decision-making?The regulatory landscape for automated decision-making, in Canada and across the world, is far from settled. Legislative and policy models are emerging, and the role of standards is evolving to support regulatory objectives. While acknowledging the contributions of leading standards development organizations, the authors argue that the rationale for standards must come from the law and that implementing such standards would help to reduce future complaints by, and would proactively enable human rights protections for, those subject to automated decision-making. The book presents a proposed standards framework for automated decision-making and provides recommendations for its implementation in the context of the government of Canadas Directive on Automated Decision-Making.As such, this book can assist public agencies around the world in developing and deploying automated decision-making systems equitably as well as being of interest to businesses that utilize automated decision-making processes. Governments around the world use machine learning in automated decision-making systems for a broad range of functions. This book seeks to answer the question: what standards should be applied to machine learning to mitigate disparate impact in automated decision-making? Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781032550220

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Heisler, Natalie; Grossman, Maura R.
Published by CRC Press, 2023
ISBN 10: 1032550228 ISBN 13: 9781032550220
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Condition: Very Good. Book is in Used-VeryGood condition. Pages and cover are clean and intact. Used items may not include supplementary materials such as CDs or access codes. May show signs of minor shelf wear and contain very limited notes and highlighting. 0.55. Seller Inventory # 1032550228-2-3

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Heisler, Natalie; Grossman, Maura R.
Published by CRC Press, 2023
ISBN 10: 1032550228 ISBN 13: 9781032550220
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Heisler, Natalie; Grossman, Maura R.
Published by CRC Press, 2023
ISBN 10: 1032550228 ISBN 13: 9781032550220
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Heisler, Natalie; Grossman, Maura R.
Published by CRC Press, 2023
ISBN 10: 1032550228 ISBN 13: 9781032550220
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Condition: Fine. Like New condition. Great condition, but not exactly fully crisp. The book may have been opened and read, but there are no defects to the book, jacket or pages. 0.55. Seller Inventory # 353-1032550228-lkn

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Heisler, Natalie; Grossman, Maura
Published by CRC Press, 2023
ISBN 10: 1032550228 ISBN 13: 9781032550220
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Natalie Heisler
Published by CRC Press, 2023
ISBN 10: 1032550228 ISBN 13: 9781032550220
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Heisler, Natalie; Grossman, Maura R.
Published by CRC Press, 2023
ISBN 10: 1032550228 ISBN 13: 9781032550220
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