Humans vs Computers is a book about ordinary people caught between wrong assumptions and computer bugs. You'll read about humans who are invisible to computers, how a default password caused a zombie apocalypse and why airlines sometimes give away free tickets. This is also a book on how to prevent, avoid and reduce the impact of such problems.

“Artificial intelligence has always inspired outlandish visions—that AI is going to destroy us, save us, or at the very least radically transform us. Erik Larson exposes the vast gap between the actual science underlying AI and the dramatic claims being made for it. This is a timely, important, and even essential book.” —John Horgan, author of The End of Science Many futurists insist that AI will soon achieve human levels of intelligence. From there, it will quickly eclipse the most gifted human mind. The Myth of Artificial Intelligence argues that such claims are just that: myths. We are not on the path to developing truly intelligent machines. We don’t even know where that path might be. Erik Larson charts a journey through the landscape of AI, from Alan Turing’s early work to today’s dominant models of machine learning. Since the beginning, AI researchers and enthusiasts have equated the reasoning approaches of AI with those of human intelligence. But this is a profound mistake. Even cutting-edge AI looks nothing like human intelligence. Modern AI is based on inductive reasoning: computers make statistical correlations to determine which answer is likely to be right, allowing software to, say, detect a particular face in an image. But human reasoning is entirely different. Humans do not correlate data sets; we make conjectures sensitive to context—the best guess, given our observations and what we already know about the world. We haven’t a clue how to program this kind of reasoning, known as abduction. Yet it is the heart of common sense. Larson argues that all this AI hype is bad science and bad for science. A culture of invention thrives on exploring unknowns, not overselling existing methods. Inductive AI will continue to improve at narrow tasks, but if we are to make real progress, we must abandon futuristic talk and learn to better appreciate the only true intelligence we know—our own.

In this follow up to Brain vs Computer: The Challenge of the Century, Jean-Pierre Fillard brings together diverse perspectives to address the recurring theme of rivalry between man and machine.Accelerated by recent events such as the Covid-19 pandemic that caught the world by surprise and brought it to a standstill, the use of technology has become more relevant than ever. What new conclusions can we draw in this debate featuring humans (brain) on the one side, and artificial intelligence (computer) on the other? Featuring brand new content including a complementary perspective from the arts, the author balances the argument from the traditional scientific approach of logic, rationality, and computation with instinct, intuition, and emotion. Read together with his latest offerings Longevity in a 2.0 World and Transhumanism: A Realistic Future? this trilogy culminates in an attempt to answer one of the most exciting questions of our time.

A playful, profound book that is not only a testament to one man's efforts to be deemed more human than a computer, but also a rollicking exploration of what it means to be human in the first place. “Terrific. ... Art and science meet an engaged mind and the friction produces real fire.” —The New Yorker Each year, the AI community convenes to administer the famous (and famously controversial) Turing test, pitting sophisticated software programs against humans to determine if a computer can “think.” The machine that most often fools the judges wins the Most Human Computer Award. But there is also a prize, strange and intriguing, for the “Most Human Human.” Brian Christian—a young poet with degrees in computer science and philosophy—was chosen to participate in a recent competition. This

The remarkable progress in algorithms for machine and deep learning have opened the doors to new opportunities, and some dark possibilities. However, a bright future awaits those who build on their working methods by including HCAI strategies of design and testing. As many technology companies and thought leaders have argued, the goal is not to replace people, but to empower them by making design choices that give humans control over technology. In Human-Centered AI, Professor Ben Shneiderman offers an optimistic realist's guide to how artificial intelligence can be used to augment and enhance humans' lives. This project bridges the gap between ethical considerations and practical realities to offer a road map for successful, reliable systems. Digital cameras, communications services, and navigation apps are just the beginning. Shneiderman shows how future applications will support health and wellness, improve education, accelerate business, and connect people in reliable, safe, and trustworthy ways that respect human values, rights, justice, and dignity.

Man vs. Machine Technology continues to advance at a rapid pace. It may sound quaint today, but not so long ago, computers battled humans for supremacy at the game of chess. The challenge of building a computer program capable of defeating the best of human-kind at chess was one of the original grand challenges of the fledgling field of artificial intelligence. On one side were dedicated scientists and hobbyists who invested decades of effort developing the software and hardware technology; on the other side were incredibly talented humans with only their determination and preparation to withstand the onslaught of technology. The man versus machine battle in chess is a landmark in the history of technology. There are numerous books that document the technical aspects of this epic story. The human side is not often told. Few chess players are inclined to write about their man-machine encounters, other than annotating the games played. This book brings the two sides together. It tells the stories of many of the key scientists and chess players that participated in a 50-year research project to advance the understanding of computing technology. “Grandmaster Karsten Müller and Professor Jonathan Schaeffer have managed to describe the fascinating history of the unequal fight of man against machine in an entertaining and instructive way. It evoked pleasant and not so pleasant memories of my own fights against the monsters. I hope that their work gives you as much pleasure as it has given me.” – From the Foreword by Vladimir Kramnik, 14th World Chess Champion

Summary Specification by Example is an emerging practice for creating software based on realistic examples, bridging the communication gap between business stakeholders and the dev teams building the software. In this book, author Gojko Adzic distills interviews with successful teams worldwide, sharing how they specify, develop, and deliver software, without defects, in short iterative delivery cycles. About the Technology Specification by Example is a collaborative method for specifying requirements and tests. Seven patterns, fully explored in this book, are key to making the method effective. The method has four main benefits: it produces living, reliable documentation; it defines expectations clearly and makes validation efficient; it reduces rework; and, above all, it assures delivery teams and business stakeholders that the software that's built is right for its purpose. About the Book This book distills from the experience of leading teams worldwide effective ways to specify, test, and deliver software in short, iterative delivery cycles. Case studies in this book range from small web startups to large financial institutions, working in many processes including XP, Scrum, and Kanban. This book is written for developers, testers, analysts, and business people working together to build great software. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book. What's Inside Common process patterns How to avoid bad practices Fitting SBE in your process 50+ case studies =============================================== Table of Contents Part 1 Getting started Part 2 Key process patterns Part 3 Case studies Key benefits Key process patterns Living documentation Initiating the changes Deriving scope from goals Specifying collaboratively Illustrating using examples Refining the specification Automating validation without changing specifications Validating frequently Evolving a documentation system uSwitch RainStor Iowa Student Loan Sabre Airline Solutions ePlan Services Songkick Concluding thoughts