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In Algorithmic Desire, Matthew Flisfeder shows that social media is a metaphor that reveals the dominant form of contemporary ideology: neoliberal capitalism. The preeminent medium of our time, social media’s digital platform and algorithmic logic shape our experience of democracy, enjoyment, and desire. Weaving between critical theory and analyses of popular culture, Flisfeder uses examples from The King’s Speech, Black Mirror, Gone Girl, The Circle, and Arrival to argue that social media highlights the antisocial dimensions of twenty‐first-century capitalism. He counters leading critical theories of social media—such as new materialism and accelerationism—and thinkers such as Gilles Deleuze and Michel Foucault, proposing instead a new structuralist account of the ideology and metaphor of social media. Emphasizing the structural role of crises, gaps, and negativity as central to our experiences of reality, Flisfeder interprets the social media metaphor through a combination of dialectical, Marxist, and Lacanian frameworks to show that algorithms may indeed read our desire, but capitalism, not social media, truly makes us antisocial. Wholly original in its interdisciplinary approach to social media and ideology, Flisfeder’s conception of “algorithmic desire” is timely, intriguing, and sure to inspire debate.
"Algorithmic Desire shows that social media is a metaphor that reveals the dominant form of contemporary ideology: neoliberal capitalism. The author interprets the social media metaphor through dialectical, Marxist, and Lacanian frameworks"--
The gap between theoretical ideas and messy reality, as seen in Neal Stephenson, Adam Smith, and Star Trek. We depend on—we believe in—algorithms to help us get a ride, choose which book to buy, execute a mathematical proof. It's as if we think of code as a magic spell, an incantation to reveal what we need to know and even what we want. Humans have always believed that certain invocations—the marriage vow, the shaman's curse—do not merely describe the world but make it. Computation casts a cultural shadow that is shaped by this long tradition of magical thinking. In this book, Ed Finn considers how the algorithm—in practical terms, “a method for solving a problem”—has its roots not only in mathematical logic but also in cybernetics, philosophy, and magical thinking. Finn argues that the algorithm deploys concepts from the idealized space of computation in a messy reality, with unpredictable and sometimes fascinating results. Drawing on sources that range from Neal Stephenson's Snow Crash to Diderot's Encyclopédie, from Adam Smith to the Star Trek computer, Finn explores the gap between theoretical ideas and pragmatic instructions. He examines the development of intelligent assistants like Siri, the rise of algorithmic aesthetics at Netflix, Ian Bogost's satiric Facebook game Cow Clicker, and the revolutionary economics of Bitcoin. He describes Google's goal of anticipating our questions, Uber's cartoon maps and black box accounting, and what Facebook tells us about programmable value, among other things. If we want to understand the gap between abstraction and messy reality, Finn argues, we need to build a model of “algorithmic reading” and scholarship that attends to process, spearheading a new experimental humanities.
Develop your own trading system with practical guidance and expert advice In Building Algorithmic Trading Systems: A Trader's Journey From Data Mining to Monte Carlo Simulation to Live Training, award-winning trader Kevin Davey shares his secrets for developing trading systems that generate triple-digit returns. With both explanation and demonstration, Davey guides you step-by-step through the entire process of generating and validating an idea, setting entry and exit points, testing systems, and implementing them in live trading. You'll find concrete rules for increasing or decreasing allocation to a system, and rules for when to abandon one. The companion website includes Davey's own Monte Carlo simulator and other tools that will enable you to automate and test your own trading ideas. A purely discretionary approach to trading generally breaks down over the long haul. With market data and statistics easily available, traders are increasingly opting to employ an automated or algorithmic trading system—enough that algorithmic trades now account for the bulk of stock trading volume. Building Algorithmic Trading Systems teaches you how to develop your own systems with an eye toward market fluctuations and the impermanence of even the most effective algorithm. Learn the systems that generated triple-digit returns in the World Cup Trading Championship Develop an algorithmic approach for any trading idea using off-the-shelf software or popular platforms Test your new system using historical and current market data Mine market data for statistical tendencies that may form the basis of a new system Market patterns change, and so do system results. Past performance isn't a guarantee of future success, so the key is to continually develop new systems and adjust established systems in response to evolving statistical tendencies. For individual traders looking for the next leap forward, Building Algorithmic Trading Systems provides expert guidance and practical advice.
“If online dating can blunt the emotional pain of separation, if adults can afford to be increasingly demanding about what they want from a relationship, the effect of online dating seems positive. But what if it’s also the case that the prospect of finding an ever more compatible mate with the click of a mouse means a future of relationship instability, a paradox of choice that keeps us chasing the illusive bunny around the dating track?” It’s the mother of all search problems: how to find a spouse, a mate, a date. The escalating marriage age and declin­ing marriage rate mean we’re spending a greater portion of our lives unattached, searching for love well into our thirties and forties. It’s no wonder that a third of America’s 90 million singles are turning to dating Web sites. Once considered the realm of the lonely and desperate, sites like eHarmony, Match, OkCupid, and Plenty of Fish have been embraced by pretty much every demographic. Thanks to the increasingly efficient algorithms that power these sites, dating has been transformed from a daunting transaction based on scarcity to one in which the possibilities are almost endless. Now anyone—young, old, straight, gay, and even married—can search for exactly what they want, connect with more people, and get more information about those people than ever before. As journalist Dan Slater shows, online dating is changing society in more profound ways than we imagine. He explores how these new technologies, by altering our perception of what’s possible, are reconditioning our feelings about commitment and challenging the traditional paradigm of adult life. Like the sexual revolution of the 1960s and ’70s, the digital revolution is forcing us to ask new questions about what constitutes “normal”: Why should we settle for someone who falls short of our expectations if there are thousands of other options just a click away? Can commitment thrive in a world of unlimited choice? Can chemistry really be quantified by math geeks? As one of Slater’s subjects wonders, “What’s the etiquette here?” Blending history, psychology, and interviews with site creators and users, Slater takes readers behind the scenes of a fascinating business. Dating sites capitalize on our quest for love, but how do their creators’ ideas about profits, morality, and the nature of desire shape the virtual worlds they’ve created for us? Should we trust an industry whose revenue model benefits from our avoiding monogamy? Documenting the untold story of the online-dating industry’s rise from ignominy to ubiquity—beginning with its early days as “computer dating” at Harvard in 1965—Slater offers a lively, entertaining, and thought provoking account of how we have, for better and worse, embraced technology in the most intimate aspect of our lives.
The gap between theoretical ideas and messy reality, as seen in Neal Stephenson, Adam Smith, and Star Trek. We depend on—we believe in—algorithms to help us get a ride, choose which book to buy, execute a mathematical proof. It's as if we think of code as a magic spell, an incantation to reveal what we need to know and even what we want. Humans have always believed that certain invocations—the marriage vow, the shaman's curse—do not merely describe the world but make it. Computation casts a cultural shadow that is shaped by this long tradition of magical thinking. In this book, Ed Finn considers how the algorithm—in practical terms, “a method for solving a problem”—has its roots not only in mathematical logic but also in cybernetics, philosophy, and magical thinking. Finn argues that the algorithm deploys concepts from the idealized space of computation in a messy reality, with unpredictable and sometimes fascinating results. Drawing on sources that range from Neal Stephenson's Snow Crash to Diderot's Encyclopédie, from Adam Smith to the Star Trek computer, Finn explores the gap between theoretical ideas and pragmatic instructions. He examines the development of intelligent assistants like Siri, the rise of algorithmic aesthetics at Netflix, Ian Bogost's satiric Facebook game Cow Clicker, and the revolutionary economics of Bitcoin. He describes Google's goal of anticipating our questions, Uber's cartoon maps and black box accounting, and what Facebook tells us about programmable value, among other things. If we want to understand the gap between abstraction and messy reality, Finn argues, we need to build a model of “algorithmic reading” and scholarship that attends to process, spearheading a new experimental humanities.
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.
What happens when the human brain, which evolved over eons, collides with twenty-first-century technology? Machines can now push psychological buttons, stimulating and sometimes exploiting the ways people make friends, gossip with neighbors, and grow intimate with lovers. Sex robots present the humanoid face of this technological revolution—yet although it is easy to gawk at their uncanniness, more familiar technologies based in artificial intelligence and virtual reality are insinuating themselves into human interactions. Digital lovers, virtual friends, and algorithmic matchmakers help us manage our feelings in a world of cognitive overload. Will these machines, fueled by masses of user data and powered by algorithms that learn all the time, transform the quality of human life? Artificial Intimacy offers an innovative perspective on the possibilities of the present and near future. The evolutionary biologist Rob Brooks explores the latest research on intimacy and desire to consider the interaction of new technologies and fundamental human behaviors. He details how existing artificial intelligences can already learn and exploit human social needs—and are getting better at what they do. Brooks combines an understanding of core human traits from evolutionary biology with analysis of how cultural, economic, and technological contexts shape the ways people express them. Beyond the technology, he asks what the implications of artificial intimacy will be for how we understand ourselves.
This book examines how algorithms in criminal justice, education, housing, elections and beyond affect autonomy, freedom, and democracy. This title is also available as Open Access on Cambridge Core.
This book analyses the changes to the regulation of everyday life that have taken place as a result of datafication, the ever-growing analytical, predictive, and structuring role of algorithms, and the prominence of the platform economy. This new form of regulation – algorithmic governance – ranges from nudging individuals towards predefined outcomes to outright structuration of behaviour through digital architecture. The author reveals the strength and pervasiveness of algorithmic politics through a comparison with the main traditional form of regulation: law. These changes are subsequently demonstrated to reflect a broader shift away from anthropocentric accounts of the world. In doing so, the book adopts a posthumanist framework which focuses on deep embeddedness and interactions between humans, the natural environment, technology, and code.