Increasingly, the decisions that affect our lives--where we go to school, whether we can get a job or a loan, how much we pay for health insurance--are being made not by humans, but by machines. In theory, this should lead to greater fairness: Everyone is judged according to the same rules.But as mathematician and data scientist Cathy O'Neil reveals, the mathematical models being used today are unregulated and uncontestable, even when they're wrong. Most troubling, they reinforce discrimination--propping up the lucky, punishing the downtrodden, and undermining our democracy in the process.

    In The Master Algorithm, Pedro Domingos lifts the veil to give us a peek inside the learning machines that power Google, Amazon, and your smartphone. He assembles a blueprint for the future universal learner--the Master Algorithm--and discusses what it will mean for business, science, and society. If data-ism is today's philosophy, this book is its bible.

    Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications.Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. The only necessary mathematical background is familiarity with elementary concepts of probability.The book is divided into three parts. Part I defines the reinforcement learning problem in terms of Markov decision processes. Part II provides basic solution methods: dynamic programming, Monte Carlo methods, and temporal-difference learning. Part III presents a unified view of the solution methods and incorporates artificial neural networks, eligibility traces, and planning; the two final chapters present case studies and consider the future of reinforcement learning.

    In Pittsburgh, a child welfare agency uses a statistical model to try to predict which children might be future victims of abuse or neglect.Since the dawn of the digital age, decision-making in finance, employment, politics, health and human services has undergone revolutionary change. Today, automated systems—rather than humans—control which neighborhoods get policed, which families attain needed resources, and who is investigated for fraud. While we all live under this new regime of data, the most invasive and punitive systems are aimed at the poor.In Automating Inequality, Virginia Eubanks systematically investigates the impacts of data mining, policy algorithms, and predictive risk models on poor and working-class people in America. The book is full of heart-wrenching and eye-opening stories, from a woman in Indiana whose benefits are literally cut off as she lays dying to a family in Pennsylvania in daily fear of losing their daughter because they fit a certain statistical profile.The U.S. has always used its most cutting-edge science and technology to contain, investigate, discipline and punish the destitute. Like the county poorhouse and scientific charity before them, digital tracking and automated decision-making hide poverty from the middle-class public and give the nation the ethical distance it needs to make inhumane choices: which families get food and which starve, who has housing and who remains homeless, and which families are broken up by the state. In the process, they weaken democracy and betray our most cherished national values.This deeply researched and passionate book could not be more timely.Naomi Klein: "This book is downright scary."Ethan Zuckerman, MIT: "Should be required reading."Dorothy Roberts, author of Killing the Black Body: "A must-read for everyone concerned about modern tools of inequality in America."Astra Taylor, author of The People's Platform: "This is the single most important book about technology you will read this year."

    Sachs-one of the world's most respected economists and the author of The New York Times bestseller The End of Poverty- offers an urgent assessment of the environmental degradation, rapid population growth, and extreme poverty that threaten global peace and prosperity. Through crystalline examination of hard facts, Sachs predicts the cascade of crises that awaits this crowded planet-and presents a program of sustainable development and international cooperation that will correct this dangerous course. Few luminaries anywhere on the planet are as schooled in this daunting subject as Sachs, and this is the vital product of his experience and wisdom.

    In this book you will find some shocking details of the great figures of science such as Newton, Galileo, Kepler, Copernicus and Kant, presented with the characteristic humor that only a popularizer of science as Sergio de Regules could bring to this wonderful collection of essays.

    You know tilt costs you money, but do you know how to make it go away? You know position is important, but do you really know how to profit from that knowledge? Elements of Poker is the distilled wisdom of a master. Published in 2007, this book is praised by poker pros worldwide as a timeless classic.

    Schumacher's riveting, richly researched statement on sustainability has become more relevant and vital with each year since its initial groundbreaking publication during the 1973 energy crisis. A landmark statement against "bigger is better" industrialism, Schumacher's Small Is Beautiful paved the way for twenty-first century books on environmentalism and economics, like Jeffrey Sachs's The End of Poverty, Paul Hawken's Natural Capitalism, Mohammad Yunis's Banker to the Poor, and Bill McKibben's Deep Economy. This timely reissue offers a crucial message for the modern world struggling to balance economic growth with the human costs of globalization.

    This includes further education, adult and community learning, work-based learning, the forces and offender learning and skills. It is easy to read with plenty of practical activities and examples throughout and the content is fully linked to the Teacher Training Standards. Please note: This book has since been updated to reflect the new title of the qualification: The Award in Education and Training.The qualification unit content contained in the appendices has since changed, and some legislation mentioned in the book has been updated.

    Reflecting the need for even minor programming in today's model-based statistics, the book pushes readers to perform step-by-step calculations that are usually automated. This unique computational approach ensures that readers understand enough of the details to make reasonable choices and interpretations in their own modeling work.The text presents generalized linear multilevel models from a Bayesian perspective, relying on a simple logical interpretation of Bayesian probability and maximum entropy. It covers from the basics of regression to multilevel models. The author also discusses measurement error, missing data, and Gaussian process models for spatial and network autocorrelation.By using complete R code examples throughout, this book provides a practical foundation for performing statistical inference. Designed for both PhD students and seasoned professionals in the natural and social sciences, it prepares them for more advanced or specialized statistical modeling.Web ResourceThe book is accompanied by an R package (rethinking) that is available on the author's website and GitHub. The two core functions (map and map2stan) of this package allow a variety of statistical models to be constructed from standard model formulas.

     When Cathy Davidson and Duke University gave free iPods to the freshman class in 2003, critics said they were wasting their money. Yet when students in practically every discipline invented academic uses for their music players, suddenly the idea could be seen in a new light-as an innovative way to turn learning on its head. This radical experiment is at the heart of Davidson's inspiring new book. Using cutting-edge research on the brain, she shows how "attention blindness" has produced one of our society's greatest challenges: while we've all acknowledged the great changes of the digital age, most of us still toil in schools and workplaces designed for the last century. Davidson introduces us to visionaries whose groundbreaking ideas-from schools with curriculums built around video games to companies that train workers using virtual environments-will open the doors to new ways of working and learning. A lively hybrid of Thomas Friedman and Norman Doidge, Now You See It is a refreshingly optimistic argument for a bold embrace of our connected, collaborative future.

    Nathan has been lying to his wife about a serious medical condition. Marsha, recently separated from her husband, cannot resist telling her children negative things about their father. What is the role of therapy in these situations? Trained to strive for neutrality and to focus strictly on the clients' needs, most therapists generally consider moral issues such as fairness, truthfulness, and obligation beyond their domain. Now, an award-winning psychologist and family therapist criticizes psychotherapy's overemphasis on individual self-interest and calls for a sense of moral responsibility in therapy.

     Develop the skills and knowledge you need to make evidence-based practice (EBP) an integral part of your clinical decision-making and everyday nursing practice with this proven, approachable text. Written in a straightforward, conversational style, Evidence-Based Practice in Nursing & Healthcare delivers real-world examples and meaningful strategies in every chapter to help you confidently meet today’s clinical challenges and ensure positive patient outcomes.NEW! Making Connections: An EBP Exemplar opens each unit, immersing you in an unfolding case study of EBP in real-life practice.NEW! Chapters reflect the most current implications of EBP on health policy and the context, content, and outcomes of implementing EBP competencies in clinical and academic settings.NEW! Learning objectives and EBP Terms to Learn at both the unit and chapter levels help you study efficiently and stay focused on essential concepts and vocabulary.Making EBP Real features continue to end each unit with real-world examples that demonstrate the principles of EBP applied.EBP Fast Facts reinforce key points at a glance.Clinical Scenarios clarify the EBP process and enhance your rapid appraisal capabilities.

    He draws on interviews with some of the world’s highest performing researchers, the literature and his own experience to identify a small number of important insights that can transform how researchers work. The book is based on an unparalleled breadth of interdisciplinary evidence that speaks directly to researchers of all disciplines and career stages. The lessons in this book will make you more productive, more satisfied with what you produce, and enable you to be happy working less, and being more. The hardback edition has the title and design imprinted on a fabric cover, hand crafted by a book maker in Yorkshire. It contains spectacular colour photography throughout. Chapters are accompanied by close-up images of trees that build up to the forest metaphor that concludes the book. These are bookended by wide perspective canopy images that accompany the front matter (from which the cover design is derived) and concluding chapter. The overall effect is a touch and feel that makes this a book to savour. Mark Reed is Professor of Socio-Technical Innovation at Newcastle University and Visiting Professor at Birmingham City University and the University of Leeds. He has over 140 publications that have been cited more than 10,000 times. He is author of The Research Impact Handbook, which he has used to train over 4000 researchers from more than 200 institutions in 55 countries.

    We all have one, but most of us will never see one. The heart surgeon now has that privilege but, for centuries, the heart was out of reach even for surgeons. So when a surgeon nowadays opens up a ribcage and mends a heart, it remains something of a miracle, even if, to some, it is merely plumbing. As with plumbers, the quality of surgeons’ work varies. As with plumbers, surgeons’ opinion of their own prowess and their own attitude to risk are not always reliable. Measurement is key. We’ve had a century of effective evidence-based medicine. We’ve had barely a decade of thorough monitoring of clinical outcomes. Thanks to the ground-breaking risk modelling of pioneering surgeons like Samer Nashef, we at last know how to judge whether an operation is in a patient’s best interest, which hospital and surgeon would be best for that operation, when it might best be performed and what the exact level of risk is. We have at last made what is important in surgery measurable. But how should surgeons, and their patients, use these newfound insights? Ever since his days as a medical student, Samer Nashef has challenged the medical profession to be more open and more accurate about the success of surgical procedures, for the sake of the patients. In The Naked Surgeon, he unclothes his own profession to demonstrate to his reader (and prospective patient) many revelations, such as the paradox at the heart of the cardiac surgeon’s craft: the more an operation is likely to kill you, the better it is for you. And he does so with absolute clarity, fluency and not a little wit.