This book is the first to examine the history of imaginative thinking about intelligent machines, featuring contributions from leading humanities and social science scholars who detail the narratives about artificial intelligence (AI) that in turn offer a crucial epistemic site for exploring contemporary debates about these powerful technologies.

This book is the first to examine the history of imaginative thinking about intelligent machines. As real Artificial Intelligence (AI) begins to touch on all aspects of our lives, this long narrative history shapes how the technology is developed, deployed and regulated. It is therefore a crucial social and ethical issue. Part I of this book provides a historical overview from ancient Greece to the start of modernity. These chapters explore the revealing pre-history of key concerns of contemporary AI discourse, from the nature of mind and creativity to issues of power and rights, from the tension between fascination and ambivalence to investigations into artificial voices and technophobia. Part II focuses on the twentieth and twenty-first-centuries in which a greater density of narratives emerge alongside rapid developments in AI technology. These chapters reveal not only how AI narratives have consistently been entangled with the emergence of real robotics and AI, but also how they offer a rich source of insight into how we might live with these revolutionary machines. Through their close textual engagements, these chapters explore the relationship between imaginative narratives and contemporary debates about AI's social, ethical and philosophical consequences, including questions of dehumanization, automation, anthropomorphisation, cybernetics, cyberpunk, immortality, slavery, and governance. The contributions, from leading humanities and social science scholars, show that narratives about AI offer a crucial epistemic site for exploring contemporary debates about these powerful new technologies.

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.

This overview of the ethical issues raised by artificial intelligence moves beyond hype and nightmare scenarios to address concrete questions—offering a compelling, necessary read for our ChatGPT era. Artificial intelligence powers Google’s search engine, enables Facebook to target advertising, and allows Alexa and Siri to do their jobs. AI is also behind self-driving cars, predictive policing, and autonomous weapons that can kill without human intervention. These and other AI applications raise complex ethical issues that are the subject of ongoing debate. This volume in the MIT Press Essential Knowledge series offers an accessible synthesis of these issues. Written by a philosopher of technology, AI Ethics goes beyond the usual hype and nightmare scenarios to address concrete questions. Mark Coeckelbergh describes influential AI narratives, ranging from Frankenstein’s monster to transhumanism and the technological singularity. He surveys relevant philosophical discussions: questions about the fundamental differences between humans and machines and debates over the moral status of AI. He explains the technology of AI, describing different approaches and focusing on machine learning and data science. He offers an overview of important ethical issues, including privacy concerns, responsibility and the delegation of decision making, transparency, and bias as it arises at all stages of data science processes. He also considers the future of work in an AI economy. Finally, he analyzes a range of policy proposals and discusses challenges for policymakers. He argues for ethical practices that embed values in design, translate democratic values into practices and include a vision of the good life and the good society.

How will AI change our world within twenty years? A pioneering technologist and acclaimed writer team up for a “dazzling” (The New York Times) look at the future that “brims with intriguing insights” (Financial Times). This edition includes a new foreword by Kai-Fu Lee. A BEST BOOK OF THE YEAR: The Wall Street Journal, The Washington Post, Financial Times Long before the advent of ChatGPT, Kai-Fu Lee and Chen Qiufan understood the enormous potential of artificial intelligence to transform our daily lives. But even as the world wakes up to the power of AI, many of us still fail to grasp the big picture. Chatbots and large language models are only the beginning. In this “inspired collaboration” (The Wall Street Journal), Lee and Chen join forces to imagine our world in 2041 and how it will be shaped by AI. In ten gripping, globe-spanning short stories and accompanying commentary, their book introduces readers to an array of eye-opening settings and characters grappling with the new abundance and potential harms of AI technologies like deep learning, mixed reality, robotics, artificial general intelligence, and autonomous weapons.

From Nobel Prize–winning economist and New York Times bestselling author Robert Shiller, a groundbreaking account of how stories help drive economic events—and why financial panics can spread like epidemic viruses Stories people tell—about financial confidence or panic, housing booms, or Bitcoin—can go viral and powerfully affect economies, but such narratives have traditionally been ignored in economics and finance because they seem anecdotal and unscientific. In this groundbreaking book, Robert Shiller explains why we ignore these stories at our peril—and how we can begin to take them seriously. Using a rich array of examples and data, Shiller argues that studying popular stories that influence individual and collective economic behavior—what he calls "narrative economics"—may vastly improve our ability to predict, prepare for, and lessen the damage of financial crises and other major economic events. The result is nothing less than a new way to think about the economy, economic change, and economics. In a new preface, Shiller reflects on some of the challenges facing narrative economics, discusses the connection between disease epidemics and economic epidemics, and suggests why epidemiology may hold lessons for fighting economic contagions.

Narrative Intelligence (NI) — the confluence of narrative, Artificial Intelligence, and media studies — studies, models, and supports the human use of narrative to understand the world. This volume brings together established work and founding documents in Narrative Intelligence to form a common reference point for NI researchers, providing perspectives from computational linguistics, agent research, psychology, ethology, art, and media theory. It describes artificial agents with narratively structured behavior, agents that take part in stories and tours, systems that automatically generate stories, dramas, and documentaries, and systems that support people telling their own stories. It looks at how people use stories, the features of narrative that play a role in how people understand the world, and how human narrative ability may have evolved. It addresses meta-issues in NI: the history of the field, the stories AI researchers tell about their research, and the effects those stories have on the things they discover. (Series B)

Zusammenfassung: This book contains best selected research papers presented at ICTCS 2023: Eighth International Conference on Information and Communication Technology for Competitive Strategies. The conference will be held in Jaipur, India during 8 - 9 December 2023. The book covers state-of-the-art as well as emerging topics pertaining to ICT and effective strategies for its implementation for engineering and managerial applications. This book contains papers mainly focused on ICT for computation, algorithms and data analytics and IT security. The work is presented in five volumes

This book explores the integration of narratology with posthumanism by examining a large scope of narratives in science fiction over nearly half a century in a range of major Anglophone countries. Based on the rhizome of posthumanism, analysis of the posthuman narrative embodiments in selected contemporary Anglophone science fiction, it investigates Ursula K. Le Guin’s The Left Hand of Darkness (1969), Ian Watson’s The Jonah Kit (1975), Iain Banks’ The Bridge (1986) and Richard Powers’ Galatea 2.2 (1995) as exemplifying various aspects of posthuman becoming-other. The book shows that, in the reactive logic of nihilism, the becoming-other posthuman, rather than posing a threat, proves to be the companion and savior of human beings, whose apocalyptic sacrifice brings back the all-too-human humanity to the chaotic world of presence.

We live in an incredible period in history. The Computer Revolution may be even more life-changing than the Industrial Revolution. We can do things with computers that could never be done before, and computers can do things for us that could never be done before. But our love of computers should not cloud our thinking about their limitations. We are told that computers are smarter than humans and that data mining can identify previously unknown truths, or make discoveries that will revolutionize our lives. Our lives may well be changed, but not necessarily for the better. Computers are very good at discovering patterns, but are useless in judging whether the unearthed patterns are sensible because computers do not think the way humans think. We fear that super-intelligent machines will decide to protect themselves by enslaving or eliminating humans. But the real danger is not that computers are smarter than us, but that we think computers are smarter than us and, so, trust computers to make important decisions for us. The AI Delusion explains why we should not be intimidated into thinking that computers are infallible, that data-mining is knowledge discovery, and that black boxes should be trusted.