Only Humans Need Apply

An invigorating, thought-provoking, and positive look at the rise of automation that explores how professionals across industries can find sustainable careers in the near future. Nearly half of all working Americans could risk losing their jobs because of technology. It’s not only blue-collar jobs at stake. Millions of educated knowledge workers—writers, paralegals, assistants, medical technicians—are threatened by accelerating advances in artificial intelligence. The industrial revolution shifted workers from farms to factories. In the first era of automation, machines relieved humans of manually exhausting work. Today, Era Two of automation continues to wash across the entire services-based economy that has replaced jobs in agriculture and manufacturing. Era Three, and the rise of AI, is dawning. Smart computers are demonstrating they are capable of making better decisions than humans. Brilliant technologies can now decide, learn, predict, and even comprehend much faster and more accurately than the human brain, and their progress is accelerating. Where will this leave lawyers, nurses, teachers, and editors? In Only Humans Need Apply, Thomas Hayes Davenport and Julia Kirby reframe the conversation about automation, arguing that the future of increased productivity and business success isn’t either human or machine. It’s both. The key is augmentation, utilizing technology to help humans work better, smarter, and faster. Instead of viewing these machines as competitive interlopers, we can see them as partners and collaborators in creative problem solving as we move into the next era. The choice is ours.

An “intriguing, insightful” look at how algorithms and robots could lead to social unrest—and how to avoid it (The Economist, Books of the Year). After decades of effort, researchers are finally cracking the code on artificial intelligence. Society stands on the cusp of unprecedented change, driven by advances in robotics, machine learning, and perception powering systems that rival or exceed human capabilities. Driverless cars, robotic helpers, and intelligent agents that promote our interests have the potential to usher in a new age of affluence and leisure—but as AI expert and Silicon Valley entrepreneur Jerry Kaplan warns, the transition may be protracted and brutal unless we address the two great scourges of the modern developed world: volatile labor markets and income inequality. In Humans Need Not Apply, he proposes innovative, free-market adjustments to our economic system and social policies to avoid an extended period of social turmoil. His timely and accessible analysis of the promises and perils of AI is a must-read for business leaders and policy makers on both sides of the aisle. “A reminder that AI systems don’t need red laser eyes to be dangerous.”—Times Higher Education Supplement “Kaplan…sidesteps the usual arguments of techno-optimism and dystopia, preferring to go for pragmatic solutions to a shrinking pool of jobs.”—Financial Times

A Wharton professor and tech entrepreneur examines how algorithms and artificial intelligence are starting to run every aspect of our lives, and how we can shape the way they impact us Through the technology embedded in almost every major tech platform and every web-enabled device, algorithms and the artificial intelligence that underlies them make a staggering number of everyday decisions for us, from what products we buy, to where we decide to eat, to how we consume our news, to whom we date, and how we find a job. We've even delegated life-and-death decisions to algorithms--decisions once made by doctors, pilots, and judges. In his new book, Kartik Hosanagar surveys the brave new world of algorithmic decision-making and reveals the potentially dangerous biases they can give rise to as they increasingly run our lives. He makes the compelling case that we need to arm ourselves with a better, deeper, more nuanced understanding of the phenomenon of algorithmic thinking. And he gives us a route in, pointing out that algorithms often think a lot like their creators--that is, like you and me. Hosanagar draws on his experiences designing algorithms professionally--as well as on history, computer science, and psychology--to explore how algorithms work and why they occasionally go rogue, what drives our trust in them, and the many ramifications of algorithmic decision-making. He examines episodes like Microsoft's chatbot Tay, which was designed to converse on social media like a teenage girl, but instead turned sexist and racist; the fatal accidents of self-driving cars; and even our own common, and often frustrating, experiences on services like Netflix and Amazon. A Human's Guide to Machine Intelligence is an entertaining and provocative look at one of the most important developments of our time and a practical user's guide to this first wave of practical artificial intelligence.

Two management and technology experts show that AI is not a job destroyer, exploring worker-AI collaboration in real-world work settings. This book breaks through both the hype and the doom-and-gloom surrounding automation and the deployment of artificial intelligence-enabled—“smart”—systems at work. Management and technology experts Thomas Davenport and Steven Miller show that, contrary to widespread predictions, prescriptions, and denunciations, AI is not primarily a job destroyer. Rather, AI changes the way we work—by taking over some tasks but not entire jobs, freeing people to do other, more important and more challenging work. By offering detailed, real-world case studies of AI-augmented jobs in settings that range from finance to the factory floor, Davenport and Miller also show that AI in the workplace is not the stuff of futuristic speculation. It is happening now to many companies and workers. These cases include a digital system for life insurance underwriting that analyzes applications and third-party data in real time, allowing human underwriters to focus on more complex cases; an intelligent telemedicine platform with a chat-based interface; a machine learning-system that identifies impending train maintenance issues by analyzing diesel fuel samples; and Flippy, a robotic assistant for fast food preparation. For each one, Davenport and Miller describe in detail the work context for the system, interviewing job incumbents, managers, and technology vendors. Short “insight” chapters draw out common themes and consider the implications of human collaboration with smart systems.

As technology races ahead, what will people do better than computers? What hope will there be for us when computers can drive cars better than humans, predict Supreme Court decisions better than legal experts, identify faces, scurry helpfully around offices and factories, even perform some surgeries, all faster, more reliably, and less expensively than people? It’s easy to imagine a nightmare scenario in which computers simply take over most of the tasks that people now get paid to do. While we’ll still need high-level decision makers and computer developers, those tasks won’t keep most working-age people employed or allow their living standard to rise. The unavoidable question—will millions of people lose out, unable to best the machine?—is increasingly dominating business, education, economics, and policy. The bestselling author of Talent Is Overrated explains how the skills the economy values are changing in historic ways. The abilities that will prove most essential to our success are no longer the technical, classroom-taught left-brain skills that economic advances have demanded from workers in the past. Instead, our greatest advantage lies in what we humans are most powerfully driven to do for and with one another, arising from our deepest, most essentially human abilities—empathy, creativity, social sensitivity, storytelling, humor, building relationships, and expressing ourselves with greater power than logic can ever achieve. This is how we create durable value that is not easily replicated by technology—because we’re hardwired to want it from humans. These high-value skills create tremendous competitive advantage—more devoted customers, stronger cultures, breakthrough ideas, and more effective teams. And while many of us regard these abilities as innate traits—“he’s a real people person,” “she’s naturally creative”—it turns out they can all be developed. They’re already being developed in a range of far-sighted organizations, such as: • the Cleveland Clinic, which emphasizes empathy training of doctors and all employees to improve patient outcomes and lower medical costs; • the U.S. Army, which has revolutionized its training to focus on human interaction, leading to stronger teams and greater success in real-world missions; • Stanford Business School, which has overhauled its curriculum to teach interpersonal skills through human-to-human experiences. As technology advances, we shouldn’t focus on beating computers at what they do—we’ll lose that contest. Instead, we must develop our most essential human abilities and teach our kids to value not just technology but also the richness of interpersonal experience. They will be the most valuable people in our world because of it. Colvin proves that to a far greater degree than most of us ever imagined, we already have what it takes to be great.

Technology advances are making tech more . . . human. This changes everything you thought you knew about innovation and strategy. In their groundbreaking book, Human + Machine, Accenture technology leaders Paul R. Daugherty and H. James Wilson showed how leading organizations use the power of human-machine collaboration to transform their processes and their bottom lines. Now, as new AI powered technologies like the metaverse, natural language processing, and digital twins begin to rapidly impact both life and work, those companies and other pioneers across industries are tipping the balance even more strikingly toward the human side with technology-led strategy that is reshaping the very nature of innovation. In Radically Human, Daugherty and Wilson show this profound shift, fast-forwarded by the pandemic, toward more human—and more humane—technology. Artificial intelligence is becoming less artificial and more intelligent. Instead of data-hungry approaches to AI, innovators are pursuing data-efficient approaches that enable machines to learn as humans do. Instead of replacing workers with machines, they're unleashing human expertise to create human-centered AI. In place of lumbering legacy IT systems, they're building cloud-first IT architectures able to continuously adapt to a world of billions of connected devices. And they're pursuing strategies that will take their place alongside classic, winning business formulas like disruptive innovation. These against-the-grain approaches to the basic building blocks of business—Intelligence, Data, Expertise, Architecture, and Strategy (IDEAS)—are transforming competition. Industrial giants and startups alike are drawing on this radically human IDEAS framework to create new business models, optimize post-pandemic approaches to work and talent, rebuild trust with their stakeholders, and show the way toward a sustainable future. With compelling insights and fresh examples from a variety of industries, Radically Human will forever change the way you think about, practice, and win with innovation.

Why do we do the things we do? Over a decade in the making, this game-changing book is Robert Sapolsky's genre-shattering attempt to answer that question as fully as perhaps only he could, looking at it from every angle. Sapolsky's storytelling concept is delightful but it also has a powerful intrinsic logic: he starts by looking at the factors that bear on a person's reaction in the precise moment a behavior occurs, and then hops back in time from there, in stages, ultimately ending up at the deep history of our species and its genetic inheritance. And so the first category of explanation is the neurobiological one. What goes on in a person's brain a second before the behavior happens? Then he pulls out to a slightly larger field of vision, a little earlier in time: What sight, sound, or smell triggers the nervous system to produce that behavior? And then, what hormones act hours to days earlier to change how responsive that individual is to the stimuli which trigger the nervous system? By now, he has increased our field of vision so that we are thinking about neurobiology and the sensory world of our environment and endocrinology in trying to explain what happened. Sapolsky keeps going--next to what features of the environment affected that person's brain, and then back to the childhood of the individual, and then to their genetic makeup. Finally, he expands the view to encompass factors larger than that one individual. How culture has shaped that individual's group, what ecological factors helped shape that culture, and on and on, back to evolutionary factors thousands and even millions of years old. The result is one of the most dazzling tours de horizon of the science of human behavior ever attempted, a majestic synthesis that harvests cutting-edge research across a range of disciplines to provide a subtle and nuanced perspective on why we ultimately do the things we do...for good and for ill. Sapolsky builds on this understanding to wrestle with some of our deepest and thorniest questions relating to tribalism and xenophobia, hierarchy and competition, morality and free will, and war and peace. Wise, humane, often very funny, Behave is a towering achievement, powerfully humanizing, and downright heroic in its own right.

You can go after the job you want…and get it! You can take the job you have…and improve it! You can take any situation you’re in…and make it work for you! Since its release in 1936, How to Win Friends and Influence People has sold more than 30 million copies. Dale Carnegie’s first book is a timeless bestseller, packed with rock-solid advice that has carried thousands of now famous people up the ladder of success in their business and personal lives. As relevant as ever before, Dale Carnegie’s principles endure, and will help you achieve your maximum potential in the complex and competitive modern age. Learn the six ways to make people like you, the twelve ways to win people to your way of thinking, and the nine ways to change people without arousing resentment.