Standards for the Control of Algorithmic Bias PDF Download

Author: Natalie Heisler
Publisher: CRC Press
ISBN: 100092758X
Category : Computers
Languages : en
Pages : 105

View

Book Description
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.

Author: Maura R. Grossman
Publisher:
ISBN: 9781003428602
Category : Algorithms
Languages : en
Pages : 0

View

Book Description
"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 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 not only to reduce future complaints, but more importantly 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 also provides recommendations for implementation in the context of Canada's Directive on Automated Decision-Making. As such, this book can assist public agencies around the world in deploying and developing automated decision-making equitably, as well as being of interest to businesses that utilize Automated Decision-Making processes"--

Author: Safiya Umoja Noble
Publisher: NYU Press
ISBN: 1479837245
Category : Computers
Languages : en
Pages : 245

View

Book Description
Acknowledgments -- Introduction: the power of algorithms -- A society, searching -- Searching for Black girls -- Searching for people and communities -- Searching for protections from search engines -- The future of knowledge in the public -- The future of information culture -- Conclusion: algorithms of oppression -- Epilogue -- Notes -- Bibliography -- Index -- About the author

Author: Michael Kearns
Publisher:
ISBN: 0190948205
Category : Business & Economics
Languages : en
Pages : 229

View

Book Description
Algorithms have made our lives more efficient and entertaining--but not without a significant cost. Can we design a better future, one in which societial gains brought about by technology are balanced with the rights of citizens? The Ethical Algorithm offers a set of principled solutions based on the emerging and exciting science of socially aware algorithm design.

Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
ISBN: 0309465052
Category : Education
Languages : en
Pages : 69

View

Book Description
The need to manage, analyze, and extract knowledge from data is pervasive across industry, government, and academia. Scientists, engineers, and executives routinely encounter enormous volumes of data, and new techniques and tools are emerging to create knowledge out of these data, some of them capable of working with real-time streams of data. The nation's ability to make use of these data depends on the availability of an educated workforce with necessary expertise. With these new capabilities have come novel ethical challenges regarding the effectiveness and appropriateness of broad applications of data analyses. The field of data science has emerged to address the proliferation of data and the need to manage and understand it. Data science is a hybrid of multiple disciplines and skill sets, draws on diverse fields (including computer science, statistics, and mathematics), encompasses topics in ethics and privacy, and depends on specifics of the domains to which it is applied. Fueled by the explosion of data, jobs that involve data science have proliferated and an array of data science programs at the undergraduate and graduate levels have been established. Nevertheless, data science is still in its infancy, which suggests the importance of envisioning what the field might look like in the future and what key steps can be taken now to move data science education in that direction. This study will set forth a vision for the emerging discipline of data science at the undergraduate level. This interim report lays out some of the information and comments that the committee has gathered and heard during the first half of its study, offers perspectives on the current state of data science education, and poses some questions that may shape the way data science education evolves in the future. The study will conclude in early 2018 with a final report that lays out a vision for future data science education.

Author: Osonde A. Osoba
Publisher: Rand Corporation
ISBN: 0833097636
Category : Computers
Languages : en
Pages : 45

View

Book Description
Machine learning algorithms and artificial intelligence influence many aspects of life today. This report identifies some of their shortcomings and associated policy risks and examines some approaches for combating these problems.

Author: Daniel Kahneman
Publisher: Little, Brown
ISBN: 031645138X
Category : Business & Economics
Languages : en
Pages : 429

View

Book Description
From the Nobel Prize-winning author of Thinking, Fast and Slow and the coauthor of Nudge, a revolutionary exploration of why people make bad judgments and how to make better ones—"a tour de force” (New York Times). Imagine that two doctors in the same city give different diagnoses to identical patients—or that two judges in the same courthouse give markedly different sentences to people who have committed the same crime. Suppose that different interviewers at the same firm make different decisions about indistinguishable job applicants—or that when a company is handling customer complaints, the resolution depends on who happens to answer the phone. Now imagine that the same doctor, the same judge, the same interviewer, or the same customer service agent makes different decisions depending on whether it is morning or afternoon, or Monday rather than Wednesday. These are examples of noise: variability in judgments that should be identical. In Noise, Daniel Kahneman, Olivier Sibony, and Cass R. Sunstein show the detrimental effects of noise in many fields, including medicine, law, economic forecasting, forensic science, bail, child protection, strategy, performance reviews, and personnel selection. Wherever there is judgment, there is noise. Yet, most of the time, individuals and organizations alike are unaware of it. They neglect noise. With a few simple remedies, people can reduce both noise and bias, and so make far better decisions. Packed with original ideas, and offering the same kinds of research-based insights that made Thinking, Fast and Slow and Nudge groundbreaking New York Times bestsellers, Noise explains how and why humans are so susceptible to noise in judgment—and what we can do about it.

Author: Khosrow-Pour D.B.A., Mehdi
Publisher: IGI Global
ISBN: 1799834743
Category : Business & Economics
Languages : en
Pages : 2734

View

Book Description
For any organization to be successful, it must operate in such a manner that knowledge and information, human resources, and technology are continually taken into consideration and managed effectively. Business concepts are always present regardless of the field or industry – in education, government, healthcare, not-for-profit, engineering, hospitality/tourism, among others. Maintaining organizational awareness and a strategic frame of mind is critical to meeting goals, gaining competitive advantage, and ultimately ensuring sustainability. The Encyclopedia of Organizational Knowledge, Administration, and Technology is an inaugural five-volume publication that offers 193 completely new and previously unpublished articles authored by leading experts on the latest concepts, issues, challenges, innovations, and opportunities covering all aspects of modern organizations. Moreover, it is comprised of content that highlights major breakthroughs, discoveries, and authoritative research results as they pertain to all aspects of organizational growth and development including methodologies that can help companies thrive and analytical tools that assess an organization’s internal health and performance. Insights are offered in key topics such as organizational structure, strategic leadership, information technology management, and business analytics, among others. The knowledge compiled in this publication is designed for entrepreneurs, managers, executives, investors, economic analysts, computer engineers, software programmers, human resource departments, and other industry professionals seeking to understand the latest tools to emerge from this field and who are looking to incorporate them in their practice. Additionally, academicians, researchers, and students in fields that include but are not limited to business, management science, organizational development, entrepreneurship, sociology, corporate psychology, computer science, and information technology will benefit from the research compiled within this publication.

Author: National Research Council
Publisher: National Academies Press
ISBN: 0309175569
Category : Social Science
Languages : en
Pages : 312

View

Book Description
Older Americans, even the oldest, can now expect to live years longer than those who reached the same ages even a few decades ago. Although survival has improved for all racial and ethnic groups, strong differences persist, both in life expectancy and in the causes of disability and death at older ages. This book examines trends in mortality rates and selected causes of disability (cardiovascular disease, dementia) for older people of different racial and ethnic groups. The determinants of these trends and differences are also investigated, including differences in access to health care and experiences in early life, diet, health behaviors, genetic background, social class, wealth and income. Groups often neglected in analyses of national data, such as the elderly Hispanic and Asian Americans of different origin and immigrant generations, are compared. The volume provides understanding of research bearing on the health status and survival of the fastest-growing segment of the American population.

Author: Stuart Jonathan Russell
Publisher: Penguin Books
ISBN: 0525558616
Category : Business & Economics
Languages : en
Pages : 354

View

Book Description
A leading artificial intelligence researcher lays out a new approach to AI that will enable people to coexist successfully with increasingly intelligent machines.