Standards for the Control of Algorithmic Bias: The Canadian Administrative Context
暫譯: 算法偏見控制標準：加拿大行政背景

Heisler, Natalie, Grossman, Maura R.

Standards for the Control of Algorithmic Bias: The Canadian Administrative Context
  • 出版商: CRC
  • 出版日期: 2023-07-04
  • 售價: $2,410
  • 貴賓價: 9.5 折 $2,290
  • 語言: 英文
  • 頁數: 96
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 1032550228
  • ISBN-13: 9781032550220
  • 相關分類: Algorithms-data-structures

    • 海外代購書籍(需單獨結帳)

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商品描述

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 Canada's 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.

商品描述(中文翻譯)

各國政府在自動化決策系統中使用機器學習來執行廣泛的功能。然而，機器學習中的演算法偏見可能導致自動化決策產生不成比例的影響，並可能妨礙《憲章》中對實質平等的保證。本書旨在回答這個問題：應該對機器學習應用什麼標準，以減輕政府在自動化決策中所造成的不成比例影響？

加拿大及全球的自動化決策的監管環境尚未確定。立法和政策模型正在出現，標準的角色也在演變，以支持監管目標。雖然承認領先的標準開發組織的貢獻，作者主張標準的理由必須來自法律，並且實施這些標準將有助於減少未來的投訴，並主動促進人權保護，特別是對於那些受到自動化決策影響的人。本書提出了一個自動化決策的標準框架，並提供了在加拿大政府自動化決策指令背景下實施的建議。

因此，本書可以幫助全球的公共機構公平地開發和部署自動化決策系統，同時也對利用自動化決策過程的企業具有參考價值。

作者簡介

Natalie Heisler has advised public- and private-sector organizations around the world in the strategy and deployment of data, analytics, and artificial intelligence for more than twenty years. Natalie brings a unique, multidisciplinary perspective to her work, spanning social, regulatory, policy, and technical dimensions. Natalie has a BA in Psychology, an MSc in Mathematics, and an MA in Political Science and lives in Toronto, Canada.

Maura R. Grossman, JD, PhD, is a research professor in the David R. Cheriton School of Computer Science at the University of Waterloo and an affiliate faculty member at the Vector Institute of Artificial Intelligence, both in Ontario, Canada. She also is principal at Maura Grossman Law, in Buffalo, New York, USA. Professor Grossman's multidisciplinary work falls at the intersection of law, health, technology, ethics, and policy.

作者簡介(中文翻譯)

Natalie Heisler 在全球的公共和私營部門組織中，已經提供了超過二十年的數據、分析和人工智慧的策略與部署建議。Natalie 將社會、法規、政策和技術等多方面的獨特跨學科視角帶入她的工作中。Natalie 擁有心理學學士學位、數學碩士學位以及政治學碩士學位，現居於加拿大多倫多。

Maura R. Grossman，法學博士、哲學博士，是加拿大安大略省滑鐵盧大學大衛·R·切里頓計算機科學學院的研究教授，同時也是人工智慧向量研究所的附屬教員。她還是美國紐約州水牛城的 Maura Grossman Law 的負責人。Grossman 教授的跨學科工作位於法律、健康、技術、倫理和政策的交匯處。

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