Jill Lepore, best-selling author of These Truths, came across the company’s papers in MIT’s archives and set out to tell this forgotten history, the long-lost backstory to the methods, and the arrogance, of Silicon Valley.Founded in 1959 by some of the nation’s leading social scientists—“the best and the brightest, fatally brilliant, Icaruses with wings of feathers and wax, flying to the sun”—Simulmatics proposed to predict and manipulate the future by way of the computer simulation of human behavior. In summers, with their wives and children in tow, the company’s scientists met on the beach in Long Island under a geodesic, honeycombed dome, where they built a “People Machine” that aimed to model everything from buying a dishwasher to counterinsurgency to casting a vote. Deploying their “People Machine” from New York, Washington, Cambridge, and even Saigon, Simulmatics’ clients included the John F. Kennedy presidential campaign, the New York Times, the Department of Defense, and dozens of major manufacturers: Simulmatics had a hand in everything from political races to the Vietnam War to the Johnson administration’s ill-fated attempt to predict race riots. The company’s collapse was almost as rapid as its ascent, a collapse that involved failed marriages, a suspicious death, and bankruptcy. Exposed for false claims, and even accused of war crimes, it closed its doors in 1970 and all but vanished. Until Lepore came across the records of its remains.The scientists of Simulmatics believed they had invented “the A-bomb of the social sciences.” They did not predict that it would take decades to detonate, like a long-buried grenade. But, in the early years of the twenty-first century, that bomb did detonate, creating a world in which corporations collect data and model behavior and target messages about the most ordinary of decisions, leaving people all over the world, long before the global pandemic, crushed by feelings of helplessness. This history has a past; If Then is its cautionary tale.

    But American engineer FREDERICK WINSLOW TAYLOR (1856-1915) broke new ground with this 1919 essay, in which he applied the rigors of scientific observation to such labor as shoveling and bricklayer in order to streamline their work... and bring a sense of logic and practicality to the management of that work. This highly influential book, must-reading for anyone seeking to understand modern management practices, puts lie to such misconceptions that making industrial processes more efficient increases unemployment and that shorter workdays decrease productivity. And it laid the foundations for the discipline of management to be studied, taught, and applied with methodical precision.

    Late fees were ubiquitous, video-streaming unheard was of, and widespread DVD adoption seemed about as imminent as flying cars. Indeed, these were the widely accepted laws of the land in 1997, when Marc Randolph had an idea. It was a simple thought—leveraging the internet to rent movies—and was just one of many more and far worse proposals, like personalized baseball bats and a shampoo delivery service, that Randolph would pitch to his business partner, Reed Hastings, on their commute to work each morning.But Hastings was intrigued, and the pair—with Hastings as the primary investor and Randolph as the CEO—founded a company. Now with over 150 million subscribers, Netflix's triumph feels inevitable, but the twenty first century's most disruptive start up began with few believers and calamity at every turn. From having to pitch his own mother on being an early investor, to the motel conference room that served as a first office, to server crashes on launch day, to the now-infamous meeting when Netflix brass pitched Blockbuster to acquire them, Marc Randolph's transformational journey exemplifies how anyone with grit, gut instincts, and determination can change the world—even with an idea that many think will never work.What emerges, though, isn't just the inside story of one of the world's most iconic companies. Full of counter-intuitive concepts and written in binge-worthy prose, it answers some of our most fundamental questions about taking that leap of faith in business or in life: How do you begin? How do you weather disappointment and failure? How do you deal with success? What even is success?From idea generation to team building to knowing when it's time to let go, That Will Never Work is not only the ultimate follow-your-dreams parable, but also one of the most dramatic and insightful entrepreneurial stories of our time.

    In Four Futures, Frase imagines how this post-capitalist world might look, deploying the tools of both social science and speculative fiction to explore what communism, rentism, socialism and exterminism might actually entail.Could the current rise of real-life robocops usher in a world that resembles Ender’s Game? And sure, communism will bring an end to material scarcities and inequalities of wealth—but there’s no guarantee that social hierarchies, governed by an economy of “likes,” wouldn’t rise to take their place. A whirlwind tour through science fiction, social theory and the new technologies already shaping our lives, Four Futures is a balance sheet of the socialisms we may reach if a resurgent Left is successful, and the barbarisms we may be consigned to if those movements fail.

    Such systems--whether political parties, stock markets, or ant colonies--present some of the most intriguing theoretical and practical challenges confronting the social sciences. Engagingly written, and balancing technical detail with intuitive explanations, Complex Adaptive Systems focuses on the key tools and ideas that have emerged in the field since the mid-1990s, as well as the techniques needed to investigate such systems. It provides a detailed introduction to concepts such as emergence, self-organized criticality, automata, networks, diversity, adaptation, and feedback. It also demonstrates how complex adaptive systems can be explored using methods ranging from mathematics to computational models of adaptive agents. John Miller and Scott Page show how to combine ideas from economics, political science, biology, physics, and computer science to illuminate topics in organization, adaptation, decentralization, and robustness. They also demonstrate how the usual extremes used in modeling can be fruitfully transcended.

    We like to think that we are in control of the future of "artificial" intelligence. The reality, though, is that we -- the everyday people whose data powers AI -- aren't actually in control of anything. When, for example, we speak with Alexa, we contribute that data to a system we can't see and have no input into -- one largely free from regulation or oversight. The big nine corporations -- Amazon, Google, Facebook, Tencent, Baidu, Alibaba, Microsoft, IBM and Apple--are the new gods of AI and are short-changing our futures to reap immediate financial gain. In this book, Amy Webb reveals the pervasive, invisible ways in which the foundations of AI -- the people working on the system, their motivations, the technology itself -- is broken. Within our lifetimes, AI will, by design, begin to behave unpredictably, thinking and acting in ways which defy human logic. The big nine corporations may be inadvertently building and enabling vast arrays of intelligent systems that don't share our motivations, desires, or hopes for the future of humanity. Much more than a passionate, human-centered call-to-arms, this book delivers a strategy for changing course, and provides a path for liberating us from algorithmic decision-makers and powerful corporations.

    In the bustling, cluttered arcades, street and interior merge and historical time is broken up into kaleidoscopic distractions and displays of ephemera. Here, at a distance from what is normally meant by "progress," Benjamin finds the lost time(s) embedded in the spaces of things.

    C. R. Licklider, whose visionary dream of a human-computer symbiosis transformed the course of modern science and led to the development of the personal computer. Reprint.

    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."

    It used to be that to diagnose an illness, interpret legal documents, analyze foreign policy, or write a newspaper article you needed a human being with specific skills—and maybe an advanced degree or two. These days, high-level tasks are increasingly being handled by algorithms that can do precise work not only with speed but also with nuance. These “bots” started with human programming and logic, but now their reach extends beyond what their creators ever expected. In this fascinating, frightening book, Christopher Steiner tells the story of how algorithms took over—and shows why the “bot revolution” is about to spill into every aspect of our lives, often silently, without our knowledge. The May 2010 “Flash Crash” exposed Wall Street’s reliance on trading bots to the tune of a 998-point market drop and $1 trillion in vanished market value. But that was just the beginning. In Automate This, we meet bots that are driving cars, penning haiku, and writing music mistaken for Bach’s. They listen in on our customer service calls and figure out what Iran would do in the event of a nuclear standoff. There are algorithms that can pick out the most cohesive crew of astronauts for a space mission or identify the next Jeremy Lin. Some can even ingest statistics from baseball games and spit out pitch-perfect sports journalism indistinguishable from that produced by humans. The interaction of man and machine can make our lives easier. But what will the world look like when algorithms control our hospitals, our roads, our culture, and our national security? What hap­pens to businesses when we automate judgment and eliminate human instinct? And what role will be left for doctors, lawyers, writers, truck drivers, and many others?  Who knows—maybe there’s a bot learning to do your job this minute.

    In Dataclysm, Christian Rudder uses it to show us who we truly are.   For centuries, we’ve relied on polling or small-scale lab experiments to study human behavior. Today, a new approach is possible. As we live more of our lives online, researchers can finally observe us directly, in vast numbers, and without filters. Data scientists have become the new demographers.   In this daring and original book, Rudder explains how Facebook "likes" can predict, with surprising accuracy, a person’s sexual orientation and even intelligence; how attractive women receive exponentially more interview requests; and why you must have haters to be hot. He charts the rise and fall of America’s most reviled word through Google Search and examines the new dynamics of collaborative rage on Twitter. He shows how people express themselves, both privately and publicly. What is the least Asian thing you can say? Do people bathe more in Vermont or New Jersey? What do black women think about Simon & Garfunkel? (Hint: they don’t think about Simon & Garfunkel.) Rudder also traces human migration over time, showing how groups of people move from certain small towns to the same big cities across the globe. And he grapples with the challenge of maintaining privacy in a world where these explorations are possible.   Visually arresting and full of wit and insight, Dataclysm is a new way of seeing ourselves—a brilliant alchemy, in which math is made human and numbers become the narrative of our time.

    Designing successful products and services in the digital age requires a multi-disciplinary team with expertise in interaction design, visual design, industrial design, and other disciplines. It also takes the ability to come up with the big ideas that make a desirable product or service, as well as the skill and perseverance to execute on the thousand small ideas that get your design into the hands of users. It requires expertise in project management, user research, and consensus-building. This comprehensive, full-color volume addresses all of these and more with detailed how-to information, real-life examples, and exercises. Topics include assembling a design team, planning and conducting user research, analyzing your data and turning it into personas, using scenarios to drive requirements definition and design, collaborating in design meetings, evaluating and iterating your design, and documenting finished design in a way that works for engineers and stakeholders alike.

    "His book is very compatible with XP. It is not about drawing pictures of a domain; it is about how you think of it, the language you use to talk about it, and how you organize your software to reflect your improving understanding of it. Eric thinks that learning about your problem domain is as likely to happen at the end of your project as at the beginning, and so refactoring is a big part of his technique. "The book is a fun read. Eric has lots of interesting stories, and he has a way with words. I see this book as essential reading for software developers--it is a future classic." --Ralph Johnson, author of Design Patterns "If you don't think you are getting value from your investment in object-oriented programming, this book will tell you what you've forgotten to do. "Eric Evans convincingly argues for the importance of domain modeling as the central focus of development and provides a solid framework and set of techniques for accomplishing it. This is timeless wisdom, and will hold up long after the methodologies du jour have gone out of fashion." --Dave Collins, author of Designing Object-Oriented User Interfaces "Eric weaves real-world experience modeling--and building--business applications into a practical, useful book. Written from the perspective of a trusted practitioner, Eric's descriptions of ubiquitous language, the benefits of sharing models with users, object life-cycle management, logical and physical application structuring, and the process and results of deep refactoring are major contributions to our field." --Luke Hohmann, author of Beyond Software Architecture "This book belongs on the shelf of every thoughtful software developer." --Kent Beck "What Eric has managed to capture is a part of the design process that experienced object designers have always used, but that we have been singularly unsuccessful as a group in conveying to the rest of the industry. We've given away bits and pieces of this knowledge...but we've never organized and systematized the principles of building domain logic. This book is important." --Kyle Brown, author of Enterprise Java(TM) Programming with IBM(R) WebSphere(R) The software development community widely acknowledges that domain modeling is central to software design. Through domain models, software developers are able to express rich functionality and translate it into a software implementation that truly serves the needs of its users. But despite its obvious importance, there are few practical resources that explain how to incorporate effective domain modeling into the software development process. Domain-Driven Design fills that need. This is not a book about specific technologies. It offers readers a systematic approach to domain-driven design, presenting an extensive set of design best practices, experience-based techniques, and fundamental principles that facilitate the development of software projects facing complex domains. Intertwining design and development practice, this book incorporates numerous examples based on actual projects to illustrate the application of domain-driven design to real-world software development. Readers learn how to use a domain model to make a complex development effort more focused and dynamic. A core of best practices and standard patterns provides a common language for the development team. A shift in emphasis--refactoring not just the code but the model underlying the code--in combination with the frequent iterations of Agile development leads to deeper insight into domains and enhanced communication between domain expert and programmer. Domain-Driven Design then builds on this foundation, and addresses modeling and design for complex systems and larger organizations.Specific topics covered include:Getting all team members to speak the same language Connecting model and implementation more deeply Sharpening key distinctions in a model Managing the lifecycle of a domain object Writing domain code that is safe to combine in elaborate ways Making complex code obvious and predictable Formulating a domain vision statement Distilling the core of a complex domain Digging out implicit concepts needed in the model Applying analysis patterns Relating design patterns to the model Maintaining model integrity in a large system Dealing with coexisting models on the same project Organizing systems with large-scale structures Recognizing and responding to modeling breakthroughs With this book in hand, object-oriented developers, system analysts, and designers will have the guidance they need to organize and focus their work, create rich and useful domain models, and leverage those models into quality, long-lasting software implementations.

    Hes also one of the most controversial CEOs in history, allegedly throwing epic tantrums, firing staff in elevators, and taking credit for other peoples achievements. So whats the real story? According to Leander Kahney, who has covered Jobs since the early 1990s as a reporter, editor, and book author, hes a fascinating bundle of contradictions. Hes an elitist who thinks most people are bozosbut he makes gadgets so easy to use, a bozo can master them. Hes a mercurial obsessive with a filthy temperbut he forges deep partnerships with creative geniuses like Steve Wozniak, Jonathan Ive, and John Lasseter. Hes a Buddhist and antimaterialistbut he produces mass-market products in Asian factories, and he promotes them with absolute mastery of the crassest medium, advertising. In short, Jobs has embraced the personality traits that some consider flawsnarcissism, perfectionism, total faith in his intuitionto lead Apple and Pixar to triumph against steep odds. And in the process, he has become a self-made billionaire. After interviewing more Apple insiders than any previous author, Kahney has distilled the principles that guide Jobs as he launches killer products, attracts fanatically loyal customers, and manages some of the worlds most powerful brands.

    Management is a key part of any organization, yet the discipline is often self-taught and unstructured. Getting to the good solutions of complex management challenges can make the difference between fulfillment and frustration for teams, and, ultimately, the success or failure of companies. Will Larson's An Elegant Puzzle orients around the particular challenges of engineering management--from sizing teams to technical debt to succession planning--and provides a path to the good solutions. Drawing from his experience at Digg, Uber, and Stripe, Will Larson has developed a thoughtful approach to engineering management that leaders of all levels at companies of all sizes can apply. An Elegant Puzzle balances structured principles and human-centric thinking to help any leader create more effective and rewarding organizations for engineers to thrive in.