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This book explores the psychological impact of advanced forms of artificial intelligence. How will it be to live with a superior intelligence? How will the exposure to highly developed artificial intelligence (AI) systems change human well-being? With a review of recent advancements in brain–computer interfaces, military AI, Explainable AI (XAI) and digital clones as a foundation, the experience of living with a hyperintelligence is discussed from the viewpoint of a clinical psychologist. The theory of universal solicitation is introduced, i.e. the demand character of a technology that wants to be used in all aspects of life. With a focus on human experience, and to a lesser extent on technology, the book is written for a general readership with an interest in psychology, technology and the future of our human condition. With its unique focus on psychological topics, the book offers contributions to a discussion on the future of human life beyond purely technological considerations.
This book explores the subject of artificial psychology and how the field must adapt human neuro-psychological testing techniques to provide adequate cognitive testing of advanced artificial intelligence systems. It shows how classical testing methods will reveal nothing about the cognitive nature of the systems and whether they are learning, reasoning, and evolving correctly; for these systems, the authors outline how testing techniques similar to/adapted from human psychological testing must be adopted, particularly in understanding how the system reacts to failure or relearning something it has learned incorrectly or inferred incorrectly. The authors provide insights into future architectures/capabilities that artificial cognitive systems will possess and how we can evaluate how well they are functioning. It discusses at length the notion of human/AI communication and collaboration and explores such topics as knowledge development, knowledge modeling and ambiguity management, artificial cognition and self-evolution of learning, artificial brain components and cognitive architecture, and artificial psychological modeling. Explores the concepts of Artificial Psychology and Artificial Neuroscience as applied to advanced artificially cognitive systems; Provides insight into the world of cognitive architectures and biologically-based computing designs which will mimic human brain functionality in artificial intelligent systems of the future; Provides description and design of artificial psychological modeling to provide insight into how advanced artificial intelligent systems are learning and evolving; Explores artificial reasoning and inference architectures and the types of modeling and testing that will be required to "trust" an autonomous artificial intelligent systems.
This book explores the psychological impact of advanced forms of artificial intelligence. How will it be to live with a superior intelligence? How will the exposure to highly developed artificial intelligence (AI) systems change human well-being? With a review of recent advancements in brain–computer interfaces, military AI, Explainable AI (XAI) and digital clones as a foundation, the experience of living with a hyperintelligence is discussed from the viewpoint of a clinical psychologist. The theory of universal solicitation is introduced, i.e. the demand character of a technology that wants to be used in all aspects of life. With a focus on human experience, and to a lesser extent on technology, the book is written for a general readership with an interest in psychology, technology and the future of our human condition. With its unique focus on psychological topics, the book offers contributions to a discussion on the future of human life beyond purely technological considerations.
Artificial Intelligence in Behavioral and Mental Health Care summarizes recent advances in artificial intelligence as it applies to mental health clinical practice. Each chapter provides a technical description of the advance, review of application in clinical practice, and empirical data on clinical efficacy. In addition, each chapter includes a discussion of practical issues in clinical settings, ethical considerations, and limitations of use. The book encompasses AI based advances in decision-making, in assessment and treatment, in providing education to clients, robot assisted task completion, and the use of AI for research and data gathering. This book will be of use to mental health practitioners interested in learning about, or incorporating AI advances into their practice and for researchers interested in a comprehensive review of these advances in one source. - Summarizes AI advances for use in mental health practice - Includes advances in AI based decision-making and consultation - Describes AI applications for assessment and treatment - Details AI advances in robots for clinical settings - Provides empirical data on clinical efficacy - Explores practical issues of use in clinical settings
As man-made machines become more powerful and smarter, will their intelligence eventually exceed our own? To accurately predict how the relationship between human and artificial intelligence will change in the future, it is essential to understand the origin and limits of human intelligence. In Birth of Intelligence, distinguished neuroscientist Daeyeol Lee tackles these pressing fundamental issues. Lee reveals how intelligence is the ability of a biological agent to solve complex decision-making problems in diverse and unpredictable environments. Furthermore, understanding how intelligent behavior emerges from interaction among multiple learning systems will provide valuable insights into the ultimate nature of human intelligence.
This profoundly ambitious and original book picks its way carefully through a vast tract of forbiddingly difficult intellectual terrain.
“Only a small community has concentratedon general intelligence. No one has tried to make a thinking machine . . . The bottom line is that we really haven’t progressed too far toward a truly intelligent machine. We have collections of dumb specialists in small domains; the true majesty of general intelligence still awaits our attack. . . . We have got to get back to the deepest questions of AI and general intelligence. . . ” –MarvinMinsky as interviewed in Hal’s Legacy, edited by David Stork, 2000. Our goal in creating this edited volume has been to ?ll an apparent gap in the scienti?c literature, by providing a coherent presentation of a body of contemporary research that, in spite of its integral importance, has hitherto kept a very low pro?le within the scienti?c and intellectual community. This body of work has not been given a name before; in this book we christen it “Arti?cial General Intelligence” (AGI). What distinguishes AGI work from run-of-the-mill “arti?cial intelligence” research is that it is explicitly focused on engineering general intelligence in the short term. We have been active researchers in the AGI ?eld for many years, and it has been a pleasure to gather together papers from our colleagues working on related ideas from their own perspectives. In the Introduction we give a conceptual overview of the AGI ?eld, and also summarize and interrelate the key ideas of the papers in the subsequent chapters.
An Introduction to Cyberpsychology is the first book to provide a student-oriented introduction to this rapidly growing and increasingly studied topic. It is designed to encourage students to critically evaluate the psychology of online interactions, and to develop appropriate research methodologies to complete their own work in this field. The book is comprised of four main sections: An overview of cyberpsychology and online research methodologies Social psychology in an online context The practical applications of cyberpsychology The psychological aspects of other technologies. Each chapter includes: Explanations of key terms and a glossary to facilitate understanding Content summaries to aid student learning Activity boxes, discussion questions and recommended reading to guide further study. Further resources for students and instructors are available on the book’s companion website, including audio and video links, essay questions, a multiple-choice test bank, and PowerPoint lecture slides. Uniquely combining a survey of the field with a focus on the applied areas of psychology, the book is designed to be a core text for undergraduate modules in cyberpsychology and the psychology of the internet, and a primer for students of postgraduate programs in cyberpsychology.
Experts from across all industrial-organizational (IO) psychology describe how increasingly rapid technological change has affected the field. In each chapter, authors describe how this has altered the meaning of IO research within a particular subdomain and what steps must be taken to avoid IO research from becoming obsolete. This Handbook presents a forward-looking review of IO psychology's understanding of both workplace technology and how technology is used in IO research methods. Using interdisciplinary perspectives to further this understanding and serving as a focal text from which this research will grow, it tackles three main questions facing the field. First, how has technology affected IO psychological theory and practice to date? Second, given the current trends in both research and practice, could IO psychological theories be rendered obsolete? Third, what are the highest priorities for both research and practice to ensure IO psychology remains appropriately engaged with technology moving forward?
“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.