Standards For The Control Of Algorithmic Bias
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| Author | : Natalie Heisler |
| Publisher | : CRC Press |
| Total Pages | : 105 |
| Release | : 2023-07-04 |
| Genre | : Computers |
| ISBN | : 100092758X |
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 | : |
| Total Pages | : 0 |
| Release | : 2023-09 |
| Genre | : Algorithms |
| ISBN | : 9781003428602 |
"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 |
| Total Pages | : 245 |
| Release | : 2018-02-20 |
| Genre | : Computers |
| ISBN | : 1479837245 |
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 | : |
| Total Pages | : 229 |
| Release | : 2020 |
| Genre | : Business & Economics |
| ISBN | : 0190948205 |
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 |
| Total Pages | : 69 |
| Release | : 2018-03-05 |
| Genre | : Education |
| ISBN | : 0309465052 |
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 |
| Total Pages | : 45 |
| Release | : 2017-04-05 |
| Genre | : Computers |
| ISBN | : 0833097636 |
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 | : Woodrow Barfield |
| Publisher | : Cambridge University Press |
| Total Pages | : 1327 |
| Release | : 2020-11-05 |
| Genre | : Law |
| ISBN | : 1108663184 |
Algorithms are a fundamental building block of artificial intelligence - and, increasingly, society - but our legal institutions have largely failed to recognize or respond to this reality. The Cambridge Handbook of the Law of Algorithms, which features contributions from US, EU, and Asian legal scholars, discusses the specific challenges algorithms pose not only to current law, but also - as algorithms replace people as decision makers - to the foundations of society itself. The work includes wide coverage of the law as it relates to algorithms, with chapters analyzing how human biases have crept into algorithmic decision-making about who receives housing or credit, the length of sentences for defendants convicted of crimes, and many other decisions that impact constitutionally protected groups. Other issues covered in the work include the impact of algorithms on the law of free speech, intellectual property, and commercial and human rights law.
| Author | : Daniel Kahneman |
| Publisher | : Little, Brown |
| Total Pages | : 429 |
| Release | : 2021-05-18 |
| Genre | : Business & Economics |
| ISBN | : 031645138X |
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 | : National Research Council |
| Publisher | : National Academies Press |
| Total Pages | : 312 |
| Release | : 1997-09-23 |
| Genre | : Social Science |
| ISBN | : 0309175569 |
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 |
| Total Pages | : 354 |
| Release | : 2019 |
| Genre | : Business & Economics |
| ISBN | : 0525558616 |
A leading artificial intelligence researcher lays out a new approach to AI that will enable people to coexist successfully with increasingly intelligent machines.
