Great Philosophical Objections To Artificial Intelligence

Winner of the 2022 CHOICE Outstanding Academic Titles This book surveys and examines the most famous philosophical arguments against building a machine with human-level intelligence. From claims and counter-claims about the ability to implement consciousness, rationality, and meaning, to arguments about cognitive architecture, the book presents a vivid history of the clash between the philosophy and AI. Tellingly, the AI Wars are mostly quiet now. Explaining this crucial fact opens new paths to understanding the current resurgence AI (especially, deep learning AI and robotics), what happens when philosophy meets science, and the role of philosophy in the culture in which it is embedded. Organising the arguments into four core topics - 'Is AI possible', 'Architectures of the Mind', 'Mental Semantics and Mental Symbols' and 'Rationality and Creativity' - this book shows the debate that played out between the philosophers on both sides of the question, and, as well, the debate between philosophers and AI scientists and engineers building AI systems. Up-to-date and forward-looking, the book is packed with fresh insights and supporting material, including: - Accessible introductions to each war, explaining the background behind the main arguments against AI - Each chapter details what happened in the AI wars, the legacy of the attacks, and what new controversies are on the horizon. - Extensive bibliography of key readings

Winner of the 2022 CHOICE Outstanding Academic Titles This book surveys and examines the most famous philosophical arguments against building a machine with human-level intelligence. From claims and counter-claims about the ability to implement consciousness, rationality, and meaning, to arguments about cognitive architecture, the book presents a vivid history of the clash between the philosophy and AI. Tellingly, the AI Wars are mostly quiet now. Explaining this crucial fact opens new paths to understanding the current resurgence AI (especially, deep learning AI and robotics), what happens when philosophy meets science, and the role of philosophy in the culture in which it is embedded. Organising the arguments into four core topics - 'Is AI possible', 'Architectures of the Mind', 'Mental Semantics and Mental Symbols' and 'Rationality and Creativity' - this book shows the debate that played out between the philosophers on both sides of the question, and, as well, the debate between philosophers and AI scientists and engineers building AI systems. Up-to-date and forward-looking, the book is packed with fresh insights and supporting material, including: - Accessible introductions to each war, explaining the background behind the main arguments against AI - Each chapter details what happened in the AI wars, the legacy of the attacks, and what new controversies are on the horizon. - Extensive bibliography of key readings

This book deals with the major philosophical issues in the theoretical framework of Artificial Intelligence (AI) in particular and cognitive science in general. The researchers in AI are concerned with the issues of consciousness, human subjectivity, creativity, etc. Cognitive Science and AI argue that consciousness can be artificially created and comprehended in the function of robots. The robotic activities explain the mechanism involved in computation, language processing, sensing the information, etc. Contrary to this thesis, the philosophical study tries to show that human consciousness, thinking, imagination, etc. are much larger concepts and need to be delved into in the broad theoretical framework. This book is a critique of the mechanistic theory of mind. It shows the basic foundation of AI and its limitations in explaining the activities of the human mental life. Machine-functionalism fails to account for the subjective nature of consciousness and the creativity involved in the conscious acts. There are two aspects of this thesis-- the epistemological and the metaphysical. Epistemologically, the subject of consciousness intimately knows the raw feelings or the qualia. Metaphysically speaking, however, the raw feelings are real in the sense that they are part of the furniture of the mental world. Therefore, we can hardly deny that the mental world is real.

Originally published in 1987 when Artificial Intelligence (AI) was one of the most hotly debated subjects of the moment; there was widespread feeling that it was a field whose ‘time had come’, that intelligent machines lay ‘just around the corner’. Moreover, with the onset of the revolution in information technology and the proclamation from all corners that we were moving into an ‘information society’, developments in AI and advanced computing were seen in many countries as having both strategic and economic importance. Yet, aside from the glare of publicity that tends to surround new scientific ideas or technologies, it must be remembered that AI was a relative newcomer among the sciences; that it had often been the subject of bitter controversy; and that though it had been promising to create intelligent machines for some 40 years prior to publication, many believe that it had actually displayed very little substantive progress. With this background in mind, the aim of this collection of essays was to take a novel look at AI. Rather than following the path of old well-trodden arguments about definitions of intelligence or the status of computer chess programs, the objective was to bring new perspectives to the subject in order to present it in a different light. Indeed, instead of simply adding to the endless wrangling ‘for’ and ‘against’ AI, the source of such divisions is made a topic for analysis in its own right. Drawing on ideas from the philosophy and sociology of scientific knowledge, this collection therefore broke new ground. Moreover, although a great deal had been written about the social and cultural impact of AI, little had been said of the culture of AI scientists themselves – including their discourse and style of thought, as well as the choices, judgements, negotiations and competitive struggles for resources that had shaped the genesis and development of the paradigmatic structure of their discipline at the time. Yet, sociologists of science have demonstrated that the analysis of factors such as these is a necessary part of understanding the development of scientific knowledge. Hence, it was hoped that this collection would help to redress the imbalance and provide a broader and more interesting picture of AI.

Presupposing no familiarity with the technical concepts of either philosophy or computing, this clear introduction reviews the progress made in AI since the inception of the field in 1956. Copeland goes on to analyze what those working in AI must achieve before they can claim to have built a thinking machine and appraises their prospects of succeeding. There are clear introductions to connectionism and to the language of thought hypothesis which weave together material from philosophy, artificial intelligence and neuroscience. John Searle's attacks on AI and cognitive science are countered and close attention is given to foundational issues, including the nature of computation, Turing Machines, the Church-Turing Thesis and the difference between classical symbol processing and parallel distributed processing. The book also explores the possibility of machines having free will and consciousness and concludes with a discussion of in what sense the human brain may be a computer.

This book reports on the results of the third edition of the premier conference in the field of philosophy of artificial intelligence, PT-AI 2017, held on November 4 - 5, 2017 at the University of Leeds, UK. It covers: advanced knowledge on key AI concepts, including complexity, computation, creativity, embodiment, representation and superintelligence; cutting-edge ethical issues, such as the AI impact on human dignity and society, responsibilities and rights of machines, as well as AI threats to humanity and AI safety; and cutting-edge developments in techniques to achieve AI, including machine learning, neural networks, dynamical systems. The book also discusses important applications of AI, including big data analytics, expert systems, cognitive architectures, and robotics. It offers a timely, yet very comprehensive snapshot of what is going on in the field of AI, especially at the interfaces between philosophy, cognitive science, ethics and computing.