Today, encyclopedias, jetliners, operating systems, mutual funds, and many other items are being created by teams numbering in the thousands or even millions. While some leaders fear the heaving growth of these massive online communities, Wikinomics proves this fear is folly. Smart firms can harness collective capability and genius to spur innovation, growth, and success. A brilliant guide to one of the most profound changes of our time, Wikinomics challenges our most deeply-rooted assumptions about business and will prove indispensable to anyone who wants to understand competitiveness in the twenty-first century. Based on a $9 million research project led by bestselling author Don Tapscott, Wikinomics shows how masses of people can participate in the economy like never before. They are creating TV news stories, sequencing the human genome, remixing their favorite music, designing software, finding a cure for disease, editing school texts, inventing new cosmetics, or even building motorcycles. You'll read about: • Rob McEwen, the Goldcorp, Inc. CEO who used open source tactics and an online competition to save his company and breathe new life into an old-fashioned industry. • Flickr, Second Life, YouTube, and other thriving online communities that transcend social networking to pioneer a new form of collaborative production. • Mature companies like Procter & Gamble that cultivate nimble, trust-based relationships with external collaborators to form vibrant business ecosystems. An important look into the future, Wikinomics will be your road map for doing business in the twenty-first century.

    A century ago, the telegraph and the mechanical tabulator were used to tame cities of millions. Today, cellular networks and cloud computing tie together the complex choreography of mega-regions of tens of millions of people.In response, cities worldwide are deploying technology to address both the timeless challenges of government and the mounting problems posed by human settlements of previously unimaginable size and complexity. In Chicago, GPS sensors on snow plows feed a real-time "plow tracker" map that everyone can access. In Zaragoza, Spain, a "citizen card" can get you on the free city-wide Wi-Fi network, unlock a bike share, check a book out of the library, and pay for your bus ride home. In New York, a guerrilla group of citizen-scientists installed sensors in local sewers to alert you when stormwater runoff overwhelms the system, dumping waste into local waterways.As technology barons, entrepreneurs, mayors, and an emerging vanguard of civic hackers are trying to shape this new frontier, Smart Cities considers the motivations, aspirations, and shortcomings of them all while offering a new civics to guide our efforts as we build the future together, one click at a time.

    We’ve seen it in sports, and now in The Victory Lab, journalist Sasha Issenberg tells the hidden story of the analytical revolution upending the way political campaigns are run in the 21st century.     The Victory Lab follows the academics and maverick operatives rocking the war room and re-engineering a high-stakes industry previously run on little more than gut instinct and outdated assumptions. Armed with research from behavioural psychology and randomized experiments that treat voters as unwitting guinea pigs, the smartest campaigns now believe they know who you will vote for even before you do.  Issenberg tracks these fascinating techniques—which include cutting edge persuasion experiments, innovative ways to mobilize voters, heavily researched electioneering methods—and shows how our most important figures, such as Barack Obama and Mitt Romney, are putting them to use with surprising skill and alacrity.     Provocative, clear-eyed and energetically reported, The Victory Lab offers iconoclastic insights into political marketing, human decision-making, and the increasing power of analytics.

    Whether they bind computers, economies, or terrorist organizations, networks are everywhere in the real world, yet only recently have scientists attempted to explain their mysterious workings.From epidemics of disease to outbreaks of market madness, from people searching for information to firms surviving crisis and change, from the structure of personal relationships to the technological and social choices of entire societies, Watts weaves together a network of discoveries across an array of disciplines to tell the story of an explosive new field of knowledge, the people who are building it, and his own peculiar path in forging this new science.

    But, if you type in "white girls," the results are radically different. The suggested porn sites and un-moderated discussions about "why black women are so sassy" or "why black women are so angry" presents a disturbing portrait of black womanhood in modern society.In Algorithms of Oppression, Safiya Umoja Noble challenges the idea that search engines like Google offer an equal playing field for all forms of ideas, identities, and activities. Data discrimination is a real social problem; Noble argues that the combination of private interests in promoting certain sites, along with the monopoly status of a relatively small number of Internet search engines, leads to a biased set of search algorithms that privilege whiteness and discriminate against people of color, specifically women of color.Through an analysis of textual and media searches as well as extensive research on paid online advertising, Noble exposes a culture of racism and sexism in the way discoverability is created online. As search engines and their related companies grow in importance - operating as a source for email, a major vehicle for primary and secondary school learning, and beyond - understanding and reversing these disquieting trends and discriminatory practices is of utmost importance.An original, surprising and, at times, disturbing account of bias on the internet, Algorithms of Oppression contributes to our understanding of how racism is created, maintained, and disseminated in the 21st century.

    The reality is that most innovations come from a process of rigorous examination through which great ideas are identified and developed before being realized as new offerings and capabilities.This book introduces the idea of design thinking‚ the collaborative process by which the designer′s sensibilities and methods are employed to match people′s needs not only with what is technically feasible and a viable business strategy. In short‚ design thinking converts need into demand. It′s a human−centered approach to problem solving that helps people and organizations become more innovative and more creative.Design thinking is not just applicable to so−called creative industries or people who work in the design field. It′s a methodology that has been used by organizations such as Kaiser Permanente to icnrease the quality of patient care by re−examining the ways that their nurses manage shift change‚ or Kraft to rethink supply chain management. This is not a book by designers for designers; this is a book for creative leaders seeking to infuse design thinking into every level of an organization‚ product‚ or service to drive new alternatives for business and society.

    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.

    Just about everyone thinks they know how they got there. Just about everyone is wrong. For all that's been written about the Four over the last two decades, no one has captured their power and staggering success as insightfully as Scott Galloway.Instead of buying the myths these compa-nies broadcast, Galloway asks fundamental questions. How did the Four infiltrate our lives so completely that they're almost impossible to avoid (or boycott)? Why does the stock market forgive them for sins that would destroy other firms? And as they race to become the world's first trillion-dollar company, can anyone chal-lenge them?In the same irreverent style that has made him one of the world's most celebrated business professors, Galloway deconstructs the strategies of the Four that lurk beneath their shiny veneers. He shows how they manipulate the fundamental emotional needs that have driven us since our ancestors lived in caves, at a speed and scope others can't match. And he reveals how you can apply the lessons of their ascent to your own business or career.Whether you want to compete with them, do business with them, or simply live in the world they dominate, you need to understand the Four.

    But all too often, these numbers are wrong. This book is a lively guide to spotting bad statistics and learning to think critically about these influential numbers. Damned Lies and Statistics is essential reading for everyone who reads or listens to the news, for students, and for anyone who relies on statistical information to understand social problems.Joel Best bases his discussion on a wide assortment of intriguing contemporary issues that have garnered much recent media attention, including abortion, cyberporn, homelessness, the Million Man March, teen suicide, the U.S. census, and much more. Using examples from the New York Times, the Washington Post, and other major newspapers and television programs, he unravels many fascinating examples of the use, misuse, and abuse of statistical information.In this book Best shows us exactly how and why bad statistics emerge, spread, and come to shape policy debates. He recommends specific ways to detect bad statistics, and shows how to think more critically about "stat wars," or disputes over social statistics among various experts. Understanding this book does not require sophisticated mathematical knowledge; Best discusses the most basic and most easily understood forms of statistics, such as percentages, averages, and rates.This accessible book provides an alternative to either naively accepting the statistics we hear or cynically assuming that all numbers are meaningless. It shows how anyone can become a more intelligent, critical, and empowered consumer of the statistics that inundate both the social sciences and our media-saturated lives.

    It helps in the process of choosing the right statistical technique and includes a detailed guide to interpreting SPSS ouput.

    If you're looking for a book like that, put this one back on the shelf.Rework shows you a better, faster, easier way to succeed in business. Read it and you'll know why plans are actually harmful, why you don't need outside investors, and why you're better off ignoring the competition. The truth is, you need less than you think. You don't need to be a workaholic. You don't need to staff up. You don't need to waste time on paperwork or meetings. You don't even need an office. Those are all just excuses.  What you really need to do is stop talking and start working. This book shows you the way. You'll learn how to be more productive, how to get exposure without breaking the bank, and tons more counterintuitive ideas that will inspire and provoke you.With its straightforward language and easy-is-better approach, Rework is the perfect playbook for anyone who’s ever dreamed of doing it on their own. Hardcore entrepreneurs, small-business owners, people stuck in day jobs they hate, victims of "downsizing," and artists who don’t want to starve anymore will all find valuable guidance in these pages.

    It has been used to expose injustice, improve health outcomes, and topple governments. But it has also been used to discriminate, police, and surveil. This potential for good, on the one hand, and harm, on the other, makes it essential to ask: Data science by whom? Data science for whom? Data science with whose interests in mind? The narratives around big data and data science are overwhelmingly white, male, and techno-heroic. In Data Feminism, Catherine D'Ignazio and Lauren Klein present a new way of thinking about data science and data ethics—one that is informed by intersectional feminist thought.Illustrating data feminism in action, D'Ignazio and Klein show how challenges to the male/female binary can help challenge other hierarchical (and empirically wrong) classification systems. They explain how, for example, an understanding of emotion can expand our ideas about effective data visualization, and how the concept of invisible labor can expose the significant human efforts required by our automated systems. And they show why the data never, ever “speak for themselves.”Data Feminism offers strategies for data scientists seeking to learn how feminism can help them work toward justice, and for feminists who want to focus their efforts on the growing field of data science. But Data Feminism is about much more than gender. It is about power, about who has it and who doesn't, and about how those differentials of power can be challenged and changed.

    With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it.Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains:Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm Optimization algorithms that search millions of possible solutions to a problem and choose the best one Bayesian filtering, used in spam filters for classifying documents based on word types and other features Using decision trees not only to make predictions, but to model the way decisions are made Predicting numerical values rather than classifications to build price models Support vector machines to match people in online dating sites Non-negative matrix factorization to find the independent features in a dataset Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details."-- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths."-- Tim Wolters, CTO, Collective Intellect

    The novel approach taken here banishes determinants to the end of the book and focuses on the central goal of linear algebra: understanding the structure of linear operators on vector spaces. The author has taken unusual care to motivate concepts and to simplify proofs. For example, the book presents - without having defined determinants - a clean proof that every linear operator on a finite-dimensional complex vector space (or an odd-dimensional real vector space) has an eigenvalue. A variety of interesting exercises in each chapter helps students understand and manipulate the objects of linear algebra. This second edition includes a new section on orthogonal projections and minimization problems. The sections on self-adjoint operators, normal operators, and the spectral theorem have been rewritten. New examples and new exercises have been added, several proofs have been simplified, and hundreds of minor improvements have been made throughout the text.

    Progressive Insurance tracks real-time customer driving patterns and uses that information to offer rates truly commensurate with individual safety. Google accurately predicts local flu outbreaks based upon thousands of user search queries. Amazon provides remarkably insightful, relevant, and timely product recommendations to its hundreds of millions of customers. Quantcast lets companies target precise audiences and key demographics throughout the Web. NASA runs contests via gamification site TopCoder, awarding prizes to those with the most innovative and cost-effective solutions to its problems. Explorys offers penetrating and previously unknown insights into healthcare behavior.How do these organizations and municipalities do it? Technology is certainly a big part, but in each case the answer lies deeper than that. Individuals at these organizations have realized that they don't have to be Nate Silver to reap massive benefits from today's new and emerging types of data. And each of these organizations has embraced Big Data, allowing them to make astute and otherwise impossible observations, actions, and predictions.It's time to start thinking big.In Too Big to Ignore, recognized technology expert and award-winning author Phil Simon explores an unassailably important trend: Big Data, the massive amounts, new types, and multifaceted sources of information streaming at us faster than ever. Never before have we seen data with the volume, velocity, and variety of today. Big Data is no temporary blip of fad. In fact, it is only going to intensify in the coming years, and its ramifications for the future of business are impossible to overstate.Too Big to Ignore explains why Big Data is a big deal. Simon provides commonsense, jargon-free advice for people and organizations looking to understand and leverage Big Data. Rife with case studies, examples, analysis, and quotes from real-world Big Data practitioners, the book is required reading for chief executives, company owners, industry leaders, and business professionals.