Albert O. Hirschman makes a basic distinction between alternative ways of reacting to deterioration in business firms and, in general, to dissatisfaction with organizations: one, "exit," is for the member to quit the organization or for the customer to switch to the competing product, and the other, "voice," is for members or customers to agitate and exert influence for change "from within." The efficiency of the competitive mechanism, with its total reliance on exit, is questioned for certain important situations. As exit often undercuts voice while being unable to counteract decline, loyalty is seen in the function of retarding exit and of permitting voice to play its proper role. The interplay of the three concepts turns out to illuminate a wide range of economic, social, and political phenomena. As the author states in the preface, "having found my own unifying way of looking at issues as diverse as competition and the two-party system, divorce and the American character, black power and the failure of 'unhappy' top officials to resign over Vietnam, I decided to let myself go a little."

    “Big data” refers to our burgeoning ability to crunch vast collections of information, analyze it instantly, and draw sometimes profoundly surprising conclusions from it. This emerging science can translate myriad phenomena—from the price of airline tickets to the text of millions of books—into searchable form, and uses our increasing computing power to unearth epiphanies that we never could have seen before. A revolution on par with the Internet or perhaps even the printing press, big data will change the way we think about business, health, politics, education, and innovation in the years to come. It also poses fresh threats, from the inevitable end of privacy as we know it to the prospect of being penalized for things we haven’t even done yet, based on big data’s ability to predict our future behavior.In this brilliantly clear, often surprising work, two leading experts explain what big data is, how it will change our lives, and what we can do to protect ourselves from its hazards. Big Data is the first big book about the next big thing.www.big-data-book.com

    John Maynard Keynes, the mercurial Cambridge economist, believed that government had a duty to spend when others would not. He met his opposite in a little-known Austrian economics professor, Freidrich Hayek, who considered attempts to intervene both pointless and potentially dangerous. The battle lines thus drawn, Keynesian economics would dominate for decades and coincide with an era of unprecedented prosperity, but conservative economists and political leaders would eventually embrace and execute Hayek's contrary vision.From their first face-to-face encounter to the heated arguments between their ardent disciples, Nicholas Wapshott here unearths the contemporary relevance of Keynes and Hayek, as present-day arguments over the virtues of the free market and government intervention rage with the same ferocity as they did in the 1930s.

    This new translation of Volume One, the only volume to be completed and edited by Marx himself, avoids some of the mistakes that have marred earlier versions and seeks to do justice to the literary qualities of the work. The introduction is by Ernest Mandel, author of Late Capitalism, one of the only comprehensive attempts to develop the theoretical legacy of Capital.

    Polya, How to Solve It will show anyone in any field how to think straight. In lucid and appealing prose, Polya reveals how the mathematical method of demonstrating a proof or finding an unknown can be of help in attacking any problem that can be reasoned out--from building a bridge to winning a game of anagrams. Generations of readers have relished Polya's deft--indeed, brilliant--instructions on stripping away irrelevancies and going straight to the heart of the problem.

    While this has had the positive effect of equalizing access to knowledge, it also has lowered the bar on what depth of knowledge is required to consider oneself an "expert." A cult of anti-expertise sentiment has coincided with anti-intellectualism, resulting in massively viral yet poorly informed debates ranging from the anti-vaccination movement to attacks on GMOs. This surge in intellectual egalitarianism has altered the landscape of debates-all voices are equal, and "fact" is a subjective term. Browsing WebMD puts one on equal footing with doctors, and Wikipedia allows all to be foreign policy experts, scientists, and more. As Tom Nichols shows in The Death of Expertise, there are a number of reasons why this has occurred-ranging from easy access to Internet search engines to a customer satisfaction model within higher education. The product of these interrelated trends, Nichols argues, is a pervasive distrust of expertise among the public coinciding with an unfounded belief among non-experts that their opinions should have equal standing with those of the experts. The experts are not always right, of course, and Nichols discusses expert failure. The crucial point is that bad decisions by experts can and have been effectively challenged by other well-informed experts. The issue now is that the democratization of information dissemination has created an army of ill-informed citizens who denounce expertise.When challenged, non-experts resort to the false argument that the experts are often wrong. Though it may be true, but the solution is not to jettison expertise as an ideal; it is to improve our expertise. Nichols is certainly not opposed to information democratization, but rather the enlightenment people believe they achieve after superficial internet research. He shows in vivid detail the ways in which this impulse is coursing through our culture and body politic, but the larger goal is to explain the benefits that expertise and rigorous learning regimes bestow upon all societies.

    of Wisconsin-Madison) and Wichern (Texas A&M U.) present the newest edition of this college text on the statistical methods for describing and analyzing multivariate data, designed for students who have taken two or more statistics courses. The fifth edition includes the addition of seve

    To its adherents, it is an elegant statement about learning from experience. To its opponents, it is subjectivity run amok.In the first-ever account of Bayes' rule for general readers, Sharon Bertsch McGrayne explores this controversial theorem and the human obsessions surrounding it. She traces its discovery by an amateur mathematician in the 1740s through its development into roughly its modern form by French scientist Pierre Simon Laplace. She reveals why respected statisticians rendered it professionally taboo for 150 years—at the same time that practitioners relied on it to solve crises involving great uncertainty and scanty information (Alan Turing's role in breaking Germany's Enigma code during World War II), and explains how the advent of off-the-shelf computer technology in the 1980s proved to be a game-changer. Today, Bayes' rule is used everywhere from DNA de-coding to Homeland Security.Drawing on primary source material and interviews with statisticians and other scientists, The Theory That Would Not Die is the riveting account of how a seemingly simple theorem ignited one of the greatest controversies of all time.

    Lasch’s identification of narcissism as not only an individual ailment but also a burgeoning social epidemic was groundbreaking. His diagnosis of American culture is even more relevant today, predicting the limitless expansion of the anxious and grasping narcissistic self into every part of American life.The Culture of Narcissism offers an astute and urgent analysis of what we need to know in these troubled times.

    It’s time we stand face-to-digital-face with the true powers and limitations of the algorithms that already automate important decisions in healthcare, transportation, crime, and commerce. Hello World is indispensable preparation for the moral quandaries of a world run by code, and with the unfailingly entertaining Hannah Fry as our guide, we’ll be discussing these issues long after the last page is turned.

    This book tackles such questions head-on.   The authors begin with the great economist John Maynard Keynes. In 1930 Keynes predicted that, within a century, per capita income would steadily rise, people’s basic needs would be met, and no one would have to work more than fifteen hours a week. Clearly, he was wrong: though income has increased as he envisioned, our wants have seemingly gone unsatisfied, and we continue to work long hours.   The Skidelskys explain why Keynes was mistaken. Then, arguing from the premise that economics is a moral science, they trace the concept of the good life from Aristotle to the present and show how our lives over the last half century have strayed from that ideal. Finally, they issue a call to think anew about what really matters in our lives and how to attain it.   How Much Is Enough? is that rarity, a work of deep intelligence and ethical commitment accessible to all readers. It will be lauded, debated, cited, and criticized. It will not be ignored.

    Herman and Noam Chomsky show that, contrary to the usual image of the news media as cantankerous, obstinate, and ubiquitous in their search for truth and defense of justice, in their actual practice they defend the economic, social, and political agendas of the privileged groups that dominate domestic society, the state, and the global order.Based on a series of case studies—including the media’s dichotomous treatment of “worthy” versus “unworthy” victims, “legitimizing” and “meaningless” Third World elections, and devastating critiques of media coverage of the U.S. wars against Indochina—Herman and Chomsky draw on decades of criticism and research to propose a Propaganda Model to explain the media’s behavior and performance. Their new introduction updates the Propaganda Model and the earlier case studies, and it discusses several other applications. These include the manner in which the media covered the passage of the North American Free Trade Agreement and subsequent Mexican financial meltdown of 1994-1995, the media’s handling of the protests against the World Trade Organization, World Bank, and International Monetary Fund in 1999 and 2000, and the media’s treatment of the chemical industry and its regulation. What emerges from this work is a powerful assessment of how propagandistic the U.S. mass media are, how they systematically fail to live up to their self-image as providers of the kind of information that people need to make sense of the world, and how we can understand their function in a radically new way.

    This title is aimed at courses in applied econometrics, political methodology, and sociological methods or a one-year graduate course in econometrics for social scientists.

    In her study of the state of modern humanity, Hannah Arendt considers humankind from the perspective of the actions of which it is capable. The problems Arendt identified then--diminishing human agency and political freedom; the paradox that as human powers increase through technological and humanistic inquiry, we are less equipped to control the consequences of our actions—continue to confront us today.

    Conflict between humans and machines is seen as inevitable and its outcome all too predictable.In this groundbreaking book, distinguished AI researcher Stuart Russell argues that this scenario can be avoided, but only if we rethink AI from the ground up. Russell begins by exploring the idea of intelligence in humans and in machines. He describes the near-term benefits we can expect, from intelligent personal assistants to vastly accelerated scientific research, and outlines the AI breakthroughs that still have to happen before we reach superhuman AI. He also spells out the ways humans are already finding to misuse AI, from lethal autonomous weapons to viral sabotage.If the predicted breakthroughs occur and superhuman AI emerges, we will have created entities far more powerful than ourselves. How can we ensure they never, ever, have power over us? Russell suggests that we can rebuild AI on a new foundation, according to which machines are designed to be inherently uncertain about the human preferences they are required to satisfy. Such machines would be humble, altruistic, and committed to pursue our objectives, not theirs. This new foundation would allow us to create machines that are provably deferential and provably beneficial.In a 2014 editorial co-authored with Stephen Hawking, Russell wrote, "Success in creating AI would be the biggest event in human history. Unfortunately, it might also be the last." Solving the problem of control over AI is not just possible; it is the key that unlocks a future of unlimited promise.