What To Do When Machines Do Everything

“Refreshingly thought-provoking...” – The Financial Times The essential playbook for the future of your business What To Do When Machines Do Everything is a guidebook to succeeding in the next generation of the digital economy. When systems running on Artificial Intelligence can drive our cars, diagnose medical patients, and manage our finances more effectively than humans it raises profound questions on the future of work and how companies compete. Illustrated with real-world cases, data, and insight, the authors provide clear strategic guidance and actionable steps to help you and your organization move ahead in a world where exponentially developing new technologies are changing how value is created. Written by a team of business and technology expert practitioners—who also authored Code Halos: How the Digital Lives of People, Things, and Organizations are Changing the Rules of Business—this book provides a clear path to the future of your work. The first part of the book examines the once in a generation upheaval most every organization will soon face as systems of intelligence go mainstream. The authors argue that contrary to the doom and gloom that surrounds much of IT and business at the moment, we are in fact on the cusp of the biggest wave of opportunity creation since the Industrial Revolution. Next, the authors detail a clear-cut business model to help leaders take part in this coming boom; the AHEAD model outlines five strategic initiatives—Automate, Halos, Enhance, Abundance, and Discovery—that are central to competing in the next phase of global business by driving new levels of efficiency, customer intimacy and innovation. Business leaders today have two options: be swallowed up by the ongoing technological evolution, or ride the crest of the wave to new profits and better business. This book shows you how to avoid your own extinction event, and will help you; Understand the untold full extent of technology's impact on the way we work and live. Find out where we're headed, and how soon the future will arrive Leverage the new emerging paradigm into a sustainable business advantage Adopt a strategic model for winning in the new economy The digital world is already transforming how we work, live, and shop, how we are governed and entertained, and how we manage our money, health, security, and relationships. Don't let your business—or your career—get left behind. What To Do When Machines Do Everything is your strategic roadmap to a future full of possibility and success. Or peril.

A fascinating look at Artificial Intelligence, from its humble Cold War beginnings to the dazzling future that is just around the corner. When most of us think about Artificial Intelligence, our minds go straight to cyborgs, robots, and sci-fi thrillers where machines take over the world. But the truth is that Artificial Intelligence is already among us. It exists in our smartphones, fitness trackers, and refrigerators that tell us when the milk will expire. In some ways, the future people dreamed of at the World's Fair in the 1960s is already here. We're teaching our machines how to think like humans, and they're learning at an incredible rate. In Thinking Machines, technology journalist Luke Dormehl takes you through the history of AI and how it makes up the foundations of the machines that think for us today. Furthermore, Dormehl speculates on the incredible--and possibly terrifying--future that's much closer than many would imagine. This remarkable book will invite you to marvel at what now seems commonplace and to dream about a future in which the scope of humanity may need to broaden itself to include intelligent machines.

What do machines do all day? Find out in this fully illustrated book that features more than 100 machines and things that go. Little ones can explore fourteen scenes set in diverse places - including the farm, the city, the construction site, the space centre and the airport - then turn the page to find out what each machine is called, and what it is used for.

The new novel from the master storyteller is his best in years. Brilliantly McEwan, richly entertaining, a moving love story and a mystery--yet for all its gripping plotline one of the most morally layered novels written for our times, as it carries us into a provocatively real alternative history and the profound challenges of Artificial Intelligence. Set in 1980s London, the story revolves around Charlie: young and reckless, and in love with his upstairs neighbour, the enchanting Miranda whose hidden, murky past hangs between them. He has spent his inheritance on the acquisition of one of twenty-five highly developed new robotic humans--named Adam or Eve, each one beautiful, strong and clever--developed by Alan Turing after his success on the legendary WW2 Enigma codebreaking machine. As London is consumed by the huge protests over England and Argentina's Falklands War and Margaret Thatcher's jingoistic ambitions, Charlie courts Miranda, and his Adam finds himself, inevitably, central to their affair. Great novelist that he is, McEwan pulls us into the question of what it means to love, what makes us human in our fast-changing times, what might follow if a machine understands too well the human heart, and how precarious a construct is the world we live in and think we know.

A guide to understanding the inner workings and outer limits of technology and why we should never assume that computers always get it right. In Artificial Unintelligence, Meredith Broussard argues that our collective enthusiasm for applying computer technology to every aspect of life has resulted in a tremendous amount of poorly designed systems. We are so eager to do everything digitally—hiring, driving, paying bills, even choosing romantic partners—that we have stopped demanding that our technology actually work. Broussard, a software developer and journalist, reminds us that there are fundamental limits to what we can (and should) do with technology. With this book, she offers a guide to understanding the inner workings and outer limits of technology—and issues a warning that we should never assume that computers always get things right. Making a case against technochauvinism—the belief that technology is always the solution—Broussard argues that it's just not true that social problems would inevitably retreat before a digitally enabled Utopia. To prove her point, she undertakes a series of adventures in computer programming. She goes for an alarming ride in a driverless car, concluding “the cyborg future is not coming any time soon”; uses artificial intelligence to investigate why students can't pass standardized tests; deploys machine learning to predict which passengers survived the Titanic disaster; and attempts to repair the U.S. campaign finance system by building AI software. If we understand the limits of what we can do with technology, Broussard tells us, we can make better choices about what we should do with it to make the world better for everyone.

"In their 'deliberately short book' IT analysts, management consultants and technology practitioners Roehrig and Pring explore how big a beast technology has become, and how we can tame it to maintain our freedom and privacy while still realising its benefits. The pandemic has shown just how much we rely on technology and how addictive it has become...The authors address the important questions...[and] urge us not to slay the monster but rather to leverage its power and reorient technology as a tool for good." —Financial Times Monster explains how we can responsibly engage with technology, and avoid its darker tendencies, while accepting its necessary gifts. The authors, insiders at one of the world's largest tech consulting firms, give a unique take on: The addictive nature of tech and how to fight it The growing backlash against big tech--where it's right and what it misses Crucial steps for taming technology's role in your life and in your organization--without becoming a modern Luddite Written for managers, leaders, and employees at companies of all sizes and in all industries, Monster will help you understand and take control of technology's powerful role in your life and your organization. "You must read this book." —Michael Schrage, Research Fellow, MIT Sloan School Initiative on the Digital Economy "Pithy insights and recommendations on helping tech fulfill its potential as a force for good." —Erik Brynjolfsson, Director of the Stanford Digital Economy Lab and co-author of The Second Machine Age "Making technology serve—not subvert—the public interest requires better leaders, not more engineers and coders. Monster explains how to become one of those leaders." —Rosabeth Moss Kanter, Harvard Business School Professor and author of Think Outside the Building "A bracing new book about some of the most pressing questions of our time." —Carl Benedikt Frey, Oxford Martin Citi Fellow at Oxford University and author of The Technology Trap "Provocative and concise, Monster is an important book on rescuing ourselves from technology that now feels corrosive and overwhelming." —Daniel H. Pink, author of WHEN, DRIVE, and TO SELL IS HUMAN "Clarifies a complex web of issues and provides bold steps for a healthier economy, society, and future." —Francisco D'Souza, former CEO and Vice Chairman of Cognizant "Sheds light on how we can collectively use technology for the good of all." —Soumitra Dutta, Founding Dean, SC Johnson College of Business, Cornell University "A cornucopia of pragmatic, actionable, and bold ideas." —Gary J. Beach, Publisher Emeritus, CIO magazine and author of U.S. Technology Skills Gap

A jaw-dropping exploration of everything that goes wrong when we build AI systems and the movement to fix them. Today’s “machine-learning” systems, trained by data, are so effective that we’ve invited them to see and hear for us—and to make decisions on our behalf. But alarm bells are ringing. Recent years have seen an eruption of concern as the field of machine learning advances. When the systems we attempt to teach will not, in the end, do what we want or what we expect, ethical and potentially existential risks emerge. Researchers call this the alignment problem. Systems cull résumés until, years later, we discover that they have inherent gender biases. Algorithms decide bail and parole—and appear to assess Black and White defendants differently. We can no longer assume that our mortgage application, or even our medical tests, will be seen by human eyes. And as autonomous vehicles share our streets, we are increasingly putting our lives in their hands. The mathematical and computational models driving these changes range in complexity from something that can fit on a spreadsheet to a complex system that might credibly be called “artificial intelligence.” They are steadily replacing both human judgment and explicitly programmed software. In best-selling author Brian Christian’s riveting account, we meet the alignment problem’s “first-responders,” and learn their ambitious plan to solve it before our hands are completely off the wheel. In a masterful blend of history and on-the ground reporting, Christian traces the explosive growth in the field of machine learning and surveys its current, sprawling frontier. Readers encounter a discipline finding its legs amid exhilarating and sometimes terrifying progress. Whether they—and we—succeed or fail in solving the alignment problem will be a defining human story. The Alignment Problem offers an unflinching reckoning with humanity’s biases and blind spots, our own unstated assumptions and often contradictory goals. A dazzlingly interdisciplinary work, it takes a hard look not only at our technology but at our culture—and finds a story by turns harrowing and hopeful.

How we can create artificial intelligence with broad, robust common sense rather than narrow, specialized expertise. It’s sometime in the not-so-distant future, and you send your fully autonomous self-driving car to the store to pick up your grocery order. The car is endowed with as much capability as an artificial intelligence agent can have, programmed to drive better than you do. But when the car encounters a traffic light stuck on red, it just sits there—indefinitely. Its obstacle-avoidance, lane-following, and route-calculation capacities are all irrelevant; it fails to act because it lacks the common sense of a human driver, who would quickly figure out what’s happening and find a workaround. In Machines like Us, Ron Brachman and Hector Levesque—both leading experts in AI—consider what it would take to create machines with common sense rather than just the specialized expertise of today’s AI systems. Using the stuck traffic light and other relatable examples, Brachman and Levesque offer an accessible account of how common sense might be built into a machine. They analyze common sense in humans, explain how AI over the years has focused mainly on expertise, and suggest ways to endow an AI system with both common sense and effective reasoning. Finally, they consider the critical issue of how we can trust an autonomous machine to make decisions, identifying two fundamental requirements for trustworthy autonomous AI systems: having reasons for doing what they do, and being able to accept advice. Both in the end are dependent on having common sense.