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The Ethical Algorithm
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Book Synopsis The Ethical Algorithm by : Michael Kearns
Download or read book The Ethical Algorithm written by Michael Kearns and published by Oxford University Press. This book was released on 2019-10-04 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the course of a generation, algorithms have gone from mathematical abstractions to powerful mediators of daily life. Algorithms have made our lives more efficient, more entertaining, and, sometimes, better informed. At the same time, complex algorithms are increasingly violating the basic rights of individual citizens. Allegedly anonymized datasets routinely leak our most sensitive personal information; statistical models for everything from mortgages to college admissions reflect racial and gender bias. Meanwhile, users manipulate algorithms to "game" search engines, spam filters, online reviewing services, and navigation apps. Understanding and improving the science behind the algorithms that run our lives is rapidly becoming one of the most pressing issues of this century. Traditional fixes, such as laws, regulations and watchdog groups, have proven woefully inadequate. Reporting from the cutting edge of scientific research, The Ethical Algorithm offers a new approach: a set of principled solutions based on the emerging and exciting science of socially aware algorithm design. Michael Kearns and Aaron Roth explain how we can better embed human principles into machine code - without halting the advance of data-driven scientific exploration. Weaving together innovative research with stories of citizens, scientists, and activists on the front lines, The Ethical Algorithm offers a compelling vision for a future, one in which we can better protect humans from the unintended impacts of algorithms while continuing to inspire wondrous advances in technology.
Book Synopsis The Ethical Algorithm by : Michael Kearns
Download or read book The Ethical Algorithm written by Michael Kearns and published by Oxford University Press, USA. This book was released on 2019 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the course of a generation, algorithms have gone from mathematical abstractions to powerful mediators of daily life. Algorithms have made our lives more efficient, more entertaining, and, sometimes, better informed. At the same time, complex algorithms are increasingly violating the basic rights of individual citizens. Allegedly anonymized datasets routinely leak our most sensitive personal information; statistical models for everything from mortgages to college admissions reflect racial and gender bias. Meanwhile, users manipulate algorithms to "game" search engines, spam filters, online reviewing services, and navigation apps. Understanding and improving the science behind the algorithms that run our lives is rapidly becoming one of the most pressing issues of this century. Traditional fixes, such as laws, regulations and watchdog groups, have proven woefully inadequate. Reporting from the cutting edge of scientific research, The Ethical Algorithm offers a new approach: a set of principled solutions based on the emerging and exciting science of socially aware algorithm design. Michael Kearns and Aaron Roth explain how we can better embed human principles into machine code - without halting the advance of data-driven scientific exploration. Weaving together innovative research with stories of citizens, scientists, and activists on the front lines, The Ethical Algorithm offers a compelling vision for a future, one in which we can better protect humans from the unintended impacts of algorithms while continuing to inspire wondrous advances in technology.
Download or read book Ethics for Robots written by Derek Leben and published by Routledge. This book was released on 2018-07-17 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ethics for Robots describes and defends a method for designing and evaluating ethics algorithms for autonomous machines, such as self-driving cars and search and rescue drones. Derek Leben argues that such algorithms should be evaluated by how effectively they accomplish the problem of cooperation among self-interested organisms, and therefore, rather than simulating the psychological systems that have evolved to solve this problem, engineers should be tackling the problem itself, taking relevant lessons from our moral psychology. Leben draws on the moral theory of John Rawls, arguing that normative moral theories are attempts to develop optimal solutions to the problem of cooperation. He claims that Rawlsian Contractarianism leads to the ‘Maximin’ principle – the action that maximizes the minimum value – and that the Maximin principle is the most effective solution to the problem of cooperation. He contrasts the Maximin principle with other principles and shows how they can often produce non-cooperative results. Using real-world examples – such as an autonomous vehicle facing a situation where every action results in harm, home care machines, and autonomous weapons systems – Leben contrasts Rawlsian algorithms with alternatives derived from utilitarianism and natural rights libertarianism. Including chapter summaries and a glossary of technical terms, Ethics for Robots is essential reading for philosophers, engineers, computer scientists, and cognitive scientists working on the problem of ethics for autonomous systems.
Book Synopsis The Everyday Life of an Algorithm by : Daniel Neyland
Download or read book The Everyday Life of an Algorithm written by Daniel Neyland and published by Springer. This book was released on 2018-12-17 with total page 151 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book begins with an algorithm–a set of IF...THEN rules used in the development of a new, ethical, video surveillance architecture for transport hubs. Readers are invited to follow the algorithm over three years, charting its everyday life. Questions of ethics, transparency, accountability and market value must be grasped by the algorithm in a series of ever more demanding forms of experimentation. Here the algorithm must prove its ability to get a grip on everyday life if it is to become an ordinary feature of the settings where it is being put to work. Through investigating the everyday life of the algorithm, the book opens a conversation with existing social science research that tends to focus on the power and opacity of algorithms. In this book we have unique access to the algorithm’s design, development and testing, but can also bear witness to its fragility and dependency on others.
Book Synopsis A Human Algorithm by : Flynn Coleman
Download or read book A Human Algorithm written by Flynn Coleman and published by Catapult. This book was released on 2020-10-20 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: A groundbreaking narrative on the urgency of ethically designed AI and a guidebook to reimagining life in the era of intelligent technology. The Age of Intelligent Machines is upon us, and we are at a reflection point. The proliferation of fast–moving technologies, including forms of artificial intelligence akin to a new species, will cause us to confront profound questions about ourselves. The era of human intellectual superiority is ending, and we need to plan for this monumental shift. A Human Algorithm: How Artificial Intelligence Is Redefining Who We Are examines the immense impact intelligent technology will have on humanity. These machines, while challenging our personal beliefs and our socioeconomic world order, also have the potential to transform our health and well–being, alleviate poverty and suffering, and reveal the mysteries of intelligence and consciousness. International human rights attorney Flynn Coleman deftly argues that it is critical that we instill values, ethics, and morals into our robots, algorithms, and other forms of AI. Equally important, we need to develop and implement laws, policies, and oversight mechanisms to protect us from tech’s insidious threats. To realize AI’s transcendent potential, Coleman advocates for inviting a diverse group of voices to participate in designing our intelligent machines and using our moral imagination to ensure that human rights, empathy, and equity are core principles of emerging technologies. Ultimately, A Human Algorithm is a clarion call for building a more humane future and moving conscientiously into a new frontier of our own design. “[Coleman] argues that the algorithms of machine learning––if they are instilled with human ethics and values––could bring about a new era of enlightenment.” —San Francisco Chronicle
Book Synopsis Algorithmic Governance and Governance of Algorithms by : Martin Ebers
Download or read book Algorithmic Governance and Governance of Algorithms written by Martin Ebers and published by Springer Nature. This book was released on 2020-10-08 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: Algorithms are now widely employed to make decisions that have increasingly far-reaching impacts on individuals and society as a whole (“algorithmic governance”), which could potentially lead to manipulation, biases, censorship, social discrimination, violations of privacy, property rights, and more. This has sparked a global debate on how to regulate AI and robotics (“governance of algorithms”). This book discusses both of these key aspects: the impact of algorithms, and the possibilities for future regulation.
Book Synopsis Algorithms from THE BOOK by : Kenneth Lange
Download or read book Algorithms from THE BOOK written by Kenneth Lange and published by SIAM. This book was released on 2020-05-04 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: Algorithms are a dominant force in modern culture, and every indication is that they will become more pervasive, not less. The best algorithms are undergirded by beautiful mathematics. This text cuts across discipline boundaries to highlight some of the most famous and successful algorithms. Readers are exposed to the principles behind these examples and guided in assembling complex algorithms from simpler building blocks. Written in clear, instructive language within the constraints of mathematical rigor, Algorithms from THE BOOK includes a large number of classroom-tested exercises at the end of each chapter. The appendices cover background material often omitted from undergraduate courses. Most of the algorithm descriptions are accompanied by Julia code, an ideal language for scientific computing. This code is immediately available for experimentation. Algorithms from THE BOOK is aimed at first-year graduate and advanced undergraduate students. It will also serve as a convenient reference for professionals throughout the mathematical sciences, physical sciences, engineering, and the quantitative sectors of the biological and social sciences.
Book Synopsis Ethics of Data and Analytics by : Kirsten Martin
Download or read book Ethics of Data and Analytics written by Kirsten Martin and published by CRC Press. This book was released on 2022-05-12 with total page 509 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unique selling point: Applies business ethics to the use of analytics, data, and AI Core audience: Graduate and undergraduate business students Place in the market: Graduate and undergraduate textbook
Book Synopsis Algorithms of Oppression by : Safiya Umoja Noble
Download or read book Algorithms of Oppression written by Safiya Umoja Noble and published by NYU Press. This book was released on 2018-02-20 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis The Algorithmic Society by : Marc Schuilenburg
Download or read book The Algorithmic Society written by Marc Schuilenburg and published by Routledge. This book was released on 2020-12-29 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: We live in an algorithmic society. Algorithms have become the main mediator through which power is enacted in our society. This book brings together three academic fields – Public Administration, Criminal Justice and Urban Governance – into a single conceptual framework, and offers a broad cultural-political analysis, addressing critical and ethical issues of algorithms. Governments are increasingly turning towards algorithms to predict criminality, deliver public services, allocate resources, and calculate recidivism rates. Mind-boggling amounts of data regarding our daily actions are analysed to make decisions that manage, control, and nudge our behaviour in everyday life. The contributions in this book offer a broad analysis of the mechanisms and social implications of algorithmic governance. Reporting from the cutting edge of scientific research, the result is illuminating and useful for understanding the relations between algorithms and power.Topics covered include: Algorithmic governmentality Transparency and accountability Fairness in criminal justice and predictive policing Principles of good digital administration Artificial Intelligence (AI) in the smart city This book is essential reading for students and scholars of Sociology, Criminology, Public Administration, Political Sciences, and Cultural Theory interested in the integration of algorithms into the governance of society.
Book Synopsis Algorithms and Law by : Martin Ebers
Download or read book Algorithms and Law written by Martin Ebers and published by Cambridge University Press. This book was released on 2020-07-23 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: Exploring issues from big-data to robotics, this volume is the first to comprehensively examine the regulatory implications of AI technology.
Download or read book AI Ethics written by Mark Coeckelbergh and published by MIT Press. This book was released on 2020-04-07 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: This overview of the ethical issues raised by artificial intelligence moves beyond hype and nightmare scenarios to address concrete questions—offering a compelling, necessary read for our ChatGPT era. Artificial intelligence powers Google’s search engine, enables Facebook to target advertising, and allows Alexa and Siri to do their jobs. AI is also behind self-driving cars, predictive policing, and autonomous weapons that can kill without human intervention. These and other AI applications raise complex ethical issues that are the subject of ongoing debate. This volume in the MIT Press Essential Knowledge series offers an accessible synthesis of these issues. Written by a philosopher of technology, AI Ethics goes beyond the usual hype and nightmare scenarios to address concrete questions. Mark Coeckelbergh describes influential AI narratives, ranging from Frankenstein’s monster to transhumanism and the technological singularity. He surveys relevant philosophical discussions: questions about the fundamental differences between humans and machines and debates over the moral status of AI. He explains the technology of AI, describing different approaches and focusing on machine learning and data science. He offers an overview of important ethical issues, including privacy concerns, responsibility and the delegation of decision making, transparency, and bias as it arises at all stages of data science processes. He also considers the future of work in an AI economy. Finally, he analyzes a range of policy proposals and discusses challenges for policymakers. He argues for ethical practices that embed values in design, translate democratic values into practices and include a vision of the good life and the good society.
Book Synopsis Algorithms of the Intelligent Web by : Douglas McIlwraith
Download or read book Algorithms of the Intelligent Web written by Douglas McIlwraith and published by Manning. This book was released on 2016-09-08 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Algorithms of the Intelligent Web, Second Edition teaches the most important approaches to algorithmic web data analysis, enabling you to create your own machine learning applications that crunch, munge, and wrangle data collected from users, web applications, sensors and website logs. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Valuable insights are buried in the tracks web users leave as they navigate pages and applications. You can uncover them by using intelligent algorithms like the ones that have earned Facebook, Google, and Twitter a place among the giants of web data pattern extraction. About the Book Algorithms of the Intelligent Web, Second Edition teaches you how to create machine learning applications that crunch and wrangle data collected from users, web applications, and website logs. In this totally revised edition, you'll look at intelligent algorithms that extract real value from data. Key machine learning concepts are explained with code examples in Python's scikit-learn. This book guides you through algorithms to capture, store, and structure data streams coming from the web. You'll explore recommendation engines and dive into classification via statistical algorithms, neural networks, and deep learning. What's Inside Introduction to machine learning Extracting structure from data Deep learning and neural networks How recommendation engines work About the Reader Knowledge of Python is assumed. About the Authors Douglas McIlwraith is a machine learning expert and data science practitioner in the field of online advertising. Dr. Haralambos Marmanis is a pioneer in the adoption of machine learning techniques for industrial solutions. Dmitry Babenko designs applications for banking, insurance, and supply-chain management. Foreword by Yike Guo. Table of Contents Building applications for the intelligent web Extracting structure from data: clustering and transforming your data Recommending relevant content Classification: placing things where they belong Case study: click prediction for online advertising Deep learning and neural networks Making the right choice The future of the intelligent web Appendix - Capturing data on the web
Book Synopsis Power and Technology by : Faridun Sattarov
Download or read book Power and Technology written by Faridun Sattarov and published by Rowman & Littlefield. This book was released on 2019-08-06 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: The notion of technological power is fast becoming an object of both academic and policy discourses. Within such discourses one can observe several different senses of power being employed, especially when viewed from a multi-disciplinary angle. This demonstrates the need for the creation of a cross-disciplinary and integrative framework for identifying and clarifying different conceptions of the relations between technology and power. In this respect, the book aims to offer an empirically-informed philosophical framework for understanding the technological construction of power, which allows for a differentiated vocabulary for describing various senses of technological power, while bridging together social and political theory, critical studies of technology, philosophy and ethics of technology. In addition, the framework presented in this book aims to contribute to better critical and ethical evaluation of technologies and their powers. Any adequate ethics or critique of technology must be based on a better, clearer, and more nuanced and differentiated understanding of the many ways in which technology can be described as ‘powerful’.
Book Synopsis Beyond the Algorithm by : Deepa Das Acevedo
Download or read book Beyond the Algorithm written by Deepa Das Acevedo and published by Cambridge University Press. This book was released on 2020-11-05 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: Qualitative empirical research reveals that the narratives and real-life experiences defining gig work have concrete implications for law.
Book Synopsis The Alignment Problem: Machine Learning and Human Values by : Brian Christian
Download or read book The Alignment Problem: Machine Learning and Human Values written by Brian Christian and published by W. W. Norton & Company. This book was released on 2020-10-06 with total page 459 pages. Available in PDF, EPUB and Kindle. Book excerpt: A jaw-dropping exploration of everything that goes wrong when we build AI systems and the movement to fix them. Today’s “machine-learning” systems, trained by data, are so effective that we’ve invited them to see and hear for us—and to make decisions on our behalf. But alarm bells are ringing. Recent years have seen an eruption of concern as the field of machine learning advances. When the systems we attempt to teach will not, in the end, do what we want or what we expect, ethical and potentially existential risks emerge. Researchers call this the alignment problem. Systems cull résumés until, years later, we discover that they have inherent gender biases. Algorithms decide bail and parole—and appear to assess Black and White defendants differently. We can no longer assume that our mortgage application, or even our medical tests, will be seen by human eyes. And as autonomous vehicles share our streets, we are increasingly putting our lives in their hands. The mathematical and computational models driving these changes range in complexity from something that can fit on a spreadsheet to a complex system that might credibly be called “artificial intelligence.” They are steadily replacing both human judgment and explicitly programmed software. In best-selling author Brian Christian’s riveting account, we meet the alignment problem’s “first-responders,” and learn their ambitious plan to solve it before our hands are completely off the wheel. In a masterful blend of history and on-the ground reporting, Christian traces the explosive growth in the field of machine learning and surveys its current, sprawling frontier. Readers encounter a discipline finding its legs amid exhilarating and sometimes terrifying progress. Whether they—and we—succeed or fail in solving the alignment problem will be a defining human story. The Alignment Problem offers an unflinching reckoning with humanity’s biases and blind spots, our own unstated assumptions and often contradictory goals. A dazzlingly interdisciplinary work, it takes a hard look not only at our technology but at our culture—and finds a story by turns harrowing and hopeful.
Book Synopsis The Algorithmic Foundations of Differential Privacy by : Cynthia Dwork
Download or read book The Algorithmic Foundations of Differential Privacy written by Cynthia Dwork and published by . This book was released on 2014 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: The problem of privacy-preserving data analysis has a long history spanning multiple disciplines. As electronic data about individuals becomes increasingly detailed, and as technology enables ever more powerful collection and curation of these data, the need increases for a robust, meaningful, and mathematically rigorous definition of privacy, together with a computationally rich class of algorithms that satisfy this definition. Differential Privacy is such a definition. The Algorithmic Foundations of Differential Privacy starts out by motivating and discussing the meaning of differential privacy, and proceeds to explore the fundamental techniques for achieving differential privacy, and the application of these techniques in creative combinations, using the query-release problem as an ongoing example. A key point is that, by rethinking the computational goal, one can often obtain far better results than would be achieved by methodically replacing each step of a non-private computation with a differentially private implementation. Despite some powerful computational results, there are still fundamental limitations. Virtually all the algorithms discussed herein maintain differential privacy against adversaries of arbitrary computational power -- certain algorithms are computationally intensive, others are efficient. Computational complexity for the adversary and the algorithm are both discussed. The monograph then turns from fundamentals to applications other than query-release, discussing differentially private methods for mechanism design and machine learning. The vast majority of the literature on differentially private algorithms considers a single, static, database that is subject to many analyses. Differential privacy in other models, including distributed databases and computations on data streams, is discussed. The Algorithmic Foundations of Differential Privacy is meant as a thorough introduction to the problems and techniques of differential privacy, and is an invaluable reference for anyone with an interest in the topic.
