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"Fantasies of Virtual Reality strips bare the tech industry's vision of a future dominated by immersive VR experiences, challenging the utopian promises of this technology, and the claims that it will revolutionize entertainment, communication, education, and business. While VR does hold significant potential, the overhyped expectations surrounding it, from achieving true empathetic understanding to transforming traditional education and office work, are often overstated -- not to mention fraught with issues of privacy, data security, and accessibility"--

"Explores the current state of Artificial General Intelligence and what the future might hold"--

"This book introduces readers to the rich history and physics of galaxies, describing what we know about these systems as well as the mysteries we are still trying to solve"--

"A short, accessible guide to the linguistic (but also moral, political, and economic) issue of endangered languages"--

"An overview of antritrust applied specifically to the context of Big Tech companies (Facebook/Meta, Google/Alphabet, Amazon, Apple, etc.)"--

An examination of the myths of the Moon goddess and how she appeared to the original creators of those myths in ancient Greece.

How to develop robots that will be more like humans and less like computers, more social than machine-like, and more playful and less programmed.Most robots are not very friendly. They vacuum the rug, mow the lawn, dispose of bombs, even perform surgery—but they aren't good conversationalists. It's difficult to make eye contact. If the future promises more human-robot collaboration in both work and play, wouldn't it be better if the robots were less mechanical and more social? In How to Grow a Robot, Mark Lee explores how robots can be more human-like, friendly, and engaging.Developments in artificial intelligence—notably Deep Learning—are widely seen as the foundation on which our robot future will be built. These advances have already brought us self-driving cars and chess match–winning algorithms. But, Lee writes, we need robots that are perceptive, animated, and responsive—more like humans and less like computers, more social than machine-like, and more playful and less programmed. The way to achieve this, he argues, is to “grow” a robot so that it learns from experience—just as infants do.After describing “what's wrong with artificial intelligence” (one key shortcoming: it's not embodied), Lee presents a different approach to building human-like robots: developmental robotics, inspired by developmental psychology and its accounts of early infant behavior. He describes his own experiments with the iCub humanoid robot and its development from newborn helplessness to ability levels equal to a nine-month-old, explaining how the iCub learns from its own experiences. AI robots are designed to know humans as objects; developmental robots will learn empathy. Developmental robots, with an internal model of “self,” will be better interactive partners with humans. That is the kind of future technology we should work toward.

The body in dreams, myths, legends, and anecdotes of the fantastic as expressions of human corporeality.In The Body Fantastic, Frank Gonzalez-Crussi looks at the human body through the lens of dreams, myths, legends, and anecdotes of the bizarre, exploring the close connection of the fictitious and the fabulous to our conception of the body. He chronicles, among other curious cases, the man who ate everything (including boiled hedgehogs and mice on toast), the therapeutic powers of saliva, hair that burst into flames, and an "amphibian man" who lived under water. Drawing on clinical records, popular lore, and art, history, and literature, Gonzalez-Crussi considers the body in both real and imaginary dimensions.Myths and stories, Gonzalez-Crussi reminds us, are the symbolic expression of our aspirations and emotions. These fantastic tales of bodies come from the deepest regions of the human psyche. Ancient Greeks, for example, believed that the uterus wandered around inside a woman's body--an "animal within an animal." If a woman sniffed an unpleasant odor, the uterus would retreat. Organized "digestive excess" began with the eating and drinking contests of antiquity and continue through the hot-dog eating competitions of today. And the "libido-podalic association," connecting male sexuality and the foot, insinuated itself into mainstream medicine in the sixteenth century; meanwhile, the feet of women in some cultures were scrupulously kept from view. Gonzalez-Crussi shows that the many imaginary representations of the body are very much a part of our corporeality.

How we are tracked, surveilled, tantalized, and seduced by machines ranging from smart watches and Roombas to immersive art installations.Sensing machines are everywhere in our world. As we move through the day, electronic sensors and computers adjust our thermostats, guide our Roombas, count our steps, change the orientation of an image when we rotate our phones. There are more of these electronic devices in the world than there are people—in 2020, thirty to fifty billion of them (versus 7.8 billion people), with more than a trillion expected in the next decade. In Sensing Machines, Chris Salter examines how we are tracked, surveilled, tantalized, and seduced by machines ranging from smart watches and mood trackers to massive immersive art installations.Salter, an artist/scholar who has worked with sensors and computers for more than twenty years, explains that the quantification of bodies, senses, and experience did not begin with the surveillance capitalism practiced by Facebook, Amazon, Netflix, and Google but can be traced back to mathematical and statistical techniques of the nineteenth century. He describes the emergence of the “sensed self,” investigating how sensor technology has been deployed in music and gaming, programmable and immersive art environments, driving, and even eating, with e-tongues and e-noses that can taste and smell for us. Sensing technology turns our experience into data; but Salter’s story isn’t just about what these machines want from us, but what we want from them—new sensations, the thrill of the uncanny, and magic that will transport us from our daily grind.

How parenting became a verb, from Dr. Spock and June Cleaver to baby whispering and free-range kids.When did “parenting” become a verb? Why is it so hard to parent, and so rife with the possibility of failure? Sitcom families of the past—the Cleavers, the Bradys, the Conners—didn’t seem to lose any sleep about their parenting methods. Today, parents are likely to be up late, doomscrolling on parenting websites. In Long Days, Short Years, Andrew Bomback—physician, writer, and father of three young children—looks at why it can be so much fun to be a parent but, at the same time, so frustrating and difficult to parent. It’s not a “how to” book (although Bomback has read plenty of these) but a “how come” book, investigating the emergence of an immersive, all-in approach to raising children that has made parenting a competitive (and often not very enjoyable) sport. Drawing on parenting books, mommy blogs, and historical accounts of parental duties as well as novels, films, podcasts, television shows, and his own experiences as a parent, Bomback charts the cultural history of parenting as a skill to be mastered, from the laid-back Dr. Spock’s 1950s childcare bible—in some years outsold only by the actual Bible—to the more rigid training schedules of Babywise. Along the way, he considers the high costs of commercialized parenting (from the babymoon on), the pressure on mothers to have it all (and do it all), scripted parenting as laid out in How to Talk So Kids Will Listen, parenting during a pandemic, and much more.

A comprehensive introduction to new approaches in artificial intelligence and robotics that are inspired by self-organizing biological processes and structures.New approaches to artificial intelligence spring from the idea that intelligence emerges as much from cells, bodies, and societies as it does from evolution, development, and learning. Traditionally, artificial intelligence has been concerned with reproducing the abilities of human brains; newer approaches take inspiration from a wider range of biological structures that that are capable of autonomous self-organization. Examples of these new approaches include evolutionary computation and evolutionary electronics, artificial neural networks, immune systems, biorobotics, and swarm intelligence—to mention only a few. This book offers a comprehensive introduction to the emerging field of biologically inspired artificial intelligence that can be used as an upper-level text or as a reference for researchers. Each chapter presents computational approaches inspired by a different biological system; each begins with background information about the biological system and then proceeds to develop computational models that make use of biological concepts. The chapters cover evolutionary computation and electronics; cellular systems; neural systems, including neuromorphic engineering; developmental systems; immune systems; behavioral systems—including several approaches to robotics, including behavior-based, bio-mimetic, epigenetic, and evolutionary robots; and collective systems, including swarm robotics as well as cooperative and competitive co-evolving systems. Chapters end with a concluding overview and suggested reading.

Interdisciplinary approaches to identifying, understanding, and remediating people's reliance on inaccurate information that they should know to be wrong.Our lives revolve around the acquisition of information. Sometimes the information we acquire—from other people, from books, or from the media—is wrong. Studies show that people rely on such misinformation, sometimes even when they are aware that the information is inaccurate or invalid. And yet investigations of learning and knowledge acquisition largely ignore encounters with this sort of problematic material. This volume fills the gap, offering theoretical and empirical perspectives on the processing of misinformation and its consequences.The contributors, from cognitive science and education science, provide analyses that represent a variety of methodologies, theoretical orientations, and fields of expertise. The chapters describe the behavioral consequences of relying on misinformation and outline possible remediations; discuss the cognitive activities that underlie encounters with inaccuracies, investigating why reliance occurs so readily; present theoretical and philosophical considerations of the nature of inaccuracies; and offer formal, empirically driven frameworks that detail when and how inaccuracies will lead to comprehension difficulties.Contributors Peter Afflerbach, Patricia A. Alexander, Jessica J. Andrews, Peter Baggetta, Jason L. G. Braasch, Ivar Bråten, M. Anne Britt, Rainer Bromme, Luke A. Buckland, Clark A. Chinn, Byeong-Young Cho, Sidney K. D'Mello, Andrea A. diSessa, Ullrich K. H. Ecker, Arthur C. Graesser, Douglas J. Hacker, Brenda Hannon, Xiangen Hu, Maj-Britt Isberner, Koto Ishiwa, Matthew E. Jacovina, Panayiota Kendeou, Jong-Yun Kim, Stephan Lewandowsky, Elizabeth J. Marsh, Ruth Mayo, Keith K. Millis, Edward J. O'Brien, Herre van Oostendorp, José Otero, David N. Rapp, Tobias Richter, Ronald W. Rinehart, Yaacov Schul, Colleen M. Seifert, Marc Stadtler, Brent Steffens, Helge I. Strømsø, Briony Swire, Sharda Umanath

A guide to fundamental issues in designing interactive visualizations, exploring ideas of inquiry, design, structured data, and usability.Interactive visualization is emerging as a vibrant new form of communication, providing compelling presentations that allow viewers to interact directly with information in order to construct their own understandings of it. Building on a long tradition of print-based information visualization, interactive visualization utilizes the technological capabilities of computers, the Internet, and computer graphics to marshal multifaceted information in the service of making a point visually. This book offers an introduction to the field, presenting a framework for exploring historical, theoretical, and practical issues. It is not a “how-to” book tied to specific and soon-to-be-outdated software tools, but a guide to the concepts that are central to building interactive visualization projects whatever their ultimate form.The framework the book presents (known as the ASSERT model, developed by the author), allows the reader to explore the process of interactive visualization in terms of choosing good questions to ask; finding appropriate data for answering them; structuring that information; exploring and analyzing the data; representing the data visually; and telling a story using the data. Interactive visualization draws on many disciplines to inform the final representation, and the book reflects this, covering basic principles of inquiry, data structuring, information design, statistics, cognitive theory, usability, working with spreadsheets, the Internet, and storytelling.

"The history of a singular building project - the Wolkenbugel, or 'cloud iron': an enigmatic design for a horizontal skyscraper designed in the 1920s by the Russian constructivist artist and architect El Lissitzky"--

"A detailed portrait of the Beistegui Penthouse Apartment in Paris, perhaps the most celebrated modernist apartment ever produced - designed by Le Corbusier in the 1920s, but now sadly demolished"--

To harness the full power of computer technology, economists need to use a broad range of mathematical techniques. In this book, Kenneth Judd presents techniques from the numerical analysis and applied mathematics literatures and shows how to use them in economic analyses. The book is divided into five parts. Part I provides a general introduction. Part II presents basics from numerical analysis on R^n, including linear equations, iterative methods, optimization, nonlinear equations, approximation methods, numerical integration and differentiation, and Monte Carlo methods. Part III covers methods for dynamic problems, including finite difference methods, projection methods, and numerical dynamic programming. Part IV covers perturbation and asymptotic solution methods. Finally, Part V covers applications to dynamic equilibrium analysis, including solution methods for perfect foresight models and rational expectation models. A website contains supplementary material including programs and answers to exercises.

An integrated approach to the empirical application of dynamic optimization programming models, for students and researchers.This book is an effective, concise text for students and researchers that combines the tools of dynamic programming with numerical techniques and simulation-based econometric methods. Doing so, it bridges the traditional gap between theoretical and empirical research and offers an integrated framework for studying applied problems in macroeconomics and microeconomics.In part I the authors first review the formal theory of dynamic optimization; they then present the numerical tools and econometric techniques necessary to evaluate the theoretical models. In language accessible to a reader with a limited background in econometrics, they explain most of the methods used in applied dynamic research today, from the estimation of probability in a coin flip to a complicated nonlinear stochastic structural model. These econometric techniques provide the final link between the dynamic programming problem and data. Part II is devoted to the application of dynamic programming to specific areas of applied economics, including the study of business cycles, consumption, and investment behavior. In each instance the authors present the specific optimization problem as a dynamic programming problem, characterize the optimal policy functions, estimate the parameters, and use models for policy evaluation.The original contribution of Dynamic Economics: Quantitative Methods and Applications lies in the integrated approach to the empirical application of dynamic optimization programming models. This integration shows that empirical applications actually complement the underlying theory of optimization, while dynamic programming problems provide needed structure for estimation and policy evaluation.

Rigorous theory and real-world applications for modeling and analysis of the behavior of complex communicating computer systems.Complex communicating computer systems—computers connected by data networks and in constant communication with their environments—do not always behave as expected. This book introduces behavioral modeling, a rigorous approach to behavioral specification and verification of concurrent and distributed systems. It is among the very few techniques capable of modeling systems interaction at a level of abstraction sufficient for the interaction to be understood and analyzed. Offering both a mathematically grounded theory and real-world applications, the book is suitable for classroom use and as a reference for system architects.The book covers the foundation of behavioral modeling using process algebra, transition systems, abstract data types, and modal logics. Exercises and examples augment the theoretical discussion. The book introduces a modeling language, mCRL2, that enables concise descriptions of even the most intricate distributed algorithms and protocols. Using behavioral axioms and such proof methods as confluence, cones, and foci, readers will learn how to prove such algorithms equal to their specifications. Specifications in mCRL2 can be simulated, visualized, or verified against their requirements. An extensive mCRL2 toolset for mechanically verifying the requirements is freely available online; this toolset has been successfully used to design and analyze industrial software that ranges from healthcare applications to particle accelerators at CERN. Appendixes offer material on equations and notation as well as exercise solutions.

In Knowledge Machines, Eric Meyer and Ralph Schroeder argue that digital technologies have fundamentally changed research practices in the sciences, social sciences, and humanities. Meyer and Schroeder show that digital tools and data, used collectively and in distributed mode -- which they term e-research -- have transformed not just the consumption of knowledge but also the production of knowledge. Digital technologies for research are reshaping how knowledge advances in disciplines that range from physics to literary analysis. Meyer and Schroeder map the rise of digital research and offer case studies from many fields, including biomedicine, social science uses of the Web, astronomy, and large-scale textual analysis in the humanities. They consider such topics as the challenges of sharing research data and of big data approaches, disciplinary differences and new forms of interdisciplinary collaboration, the shifting boundaries between researchers and their publics, and the ways that digital tools promote openness in science.This book considers the transformations of research from a number of perspectives, drawing especially on the sociology of science and technology and social informatics. It shows that the use of digital tools and data is not just a technical issue; it affects research practices, collaboration models, publishing choices, and even the kinds of research and research questions scholars choose to pursue. Knowledge Machines examines the nature and implications of these transformations for scholarly research.

A groundbreaking framework for improving portfolio performance that goes beyond traditional analytics, offering new ways to understand investment skills, process, and behaviors.Portfolio management is a tough business. Each day, managers face the challenges of an ever-changing and unforgiving market, where strategies and processes that worked yesterday may not work today, or tomorrow. The usual advice for improving portfolio performance-refining your strategy, staying within your style, doing better research, trading more efficiently-is important, but doesn't seem to affect outcomes sufficiently. This book, by an experienced advisor to institutional money managers, goes beyond conventional thinking to offer a new analytic framework that enables investors to improve their performance confidently, deliberately, and simply, by applying the principles of behavioral finance.W. Edwards Deming observed that you can't improve what you don't measure. Active portfolio management lacks methods for measuring key inputs to management success like skills, process, and behavioral tendencies. Michael Ervolini offers a conceptually straightforward and well-tested framework that does just that, with evidence of how it helps managers enhance self-awareness and become better investors. In a series of short, accessible chapters, Ervolini investigates a range of topics from psychology and neuroscience, describing their relevance to the challenges of portfolio management. Finally, Ervolini offers seven ideas for improving. These range from maintaining an investment diary to performing rudimentary calculations that quantify basic skills; each idea, or "e;project,"e; helps managers gain a deeper understanding of their strengths and shortcomings and how to use this knowledge to improve investment performance.

The biography of a multifaceted technological object, the IUD, illuminates how political contexts shaped contraceptive development, marketing, use, and users.The intrauterine device (IUD) is used by 150 million women around the world. It is the second most prevalent method of female fertility control in the global South and the third most prevalent in the global North. Over its five decades of use, the IUD has been viewed both as a means for women's reproductive autonomy and as coercive tool of state-imposed population control, as a convenient form of birth control on a par with the pill and as a threat to women's health. In this book, Chikako Takeshita investigates the development, marketing, and use of the IUD since the 1960s. She offers a biography of a multifaceted technological object through a feminist science studies lens, tracing the transformations of the scientific discourse around it over time and across different geographies.Takeshita describes how developers of the IUD adapted to different social interests in their research and how changing assumptions about race, class, and female sexuality often guided scientific inquiries. The IUD, she argues, became a “politically versatile technology,” adaptable to both feminist and nonfeminist reproductive politics because of researchers' attempts to maintain the device's suitability for women in both the developing and the developed world. Takeshita traces the evolution of scientists' concerns—from contraceptive efficacy and product safety to the politics of abortion—and describes the most recent, hormone-releasing, menstruation-suppressing iteration of the IUD. Examining fifty years of IUD development and use, Takeshita finds a microcosm of the global political economy of women's bodies, health, and sexuality in the history of this contraceptive device.