With a 30-year career in artificial intelligence (AI) and computer science, Hall reviews the history of AI, predicting the probable achievements in the near future and provides an intriguing glimpse into the astonishing possibilities and dilemmas on the horizon.

Focuses on the definition, engineering, and delivery of AI solutions as opposed to AI itself Reader will still gain a strong understanding of AI, but through the perspective of delivering real solutions Explores the core AI issues that impact the success of an overall solution including i. realities of dealing with data, ii. impact of AI accuracy on the ability of the solution to meet business objectives, iii. challenges in managing the quality of machine learning models Includes real world examples of enterprise scale solutions Provides a series of (optional) technical deep dives and thought experiments.

The first book in the Fast Future series, Beyond Genuine Stupidity: Ensuring AI Serves Humanity, explores critical emerging issues arising from the rapid pace of development in artificial intelligence (AI). The authors argue for a forward-looking and conscious approach to the development and deployment of AI to ensure that it genuinely serves humanity's best interest. Through a series of articles, they present a compelling case to get beyond the genuine stupidity of narrow, short-term and alarmist thinking and look at AI from a long-term holistic perspective. The reality is that AI will impact current sectors and jobs—and hopefully enable new ones. A smart approach requires us to think about and experiment with strategies for adopting and absorbing the impacts of AI—encompassing education systems, reskilling the workforce, unemployment and guaranteed basic incomes, robot taxes, job creation, encouraging new ventures, research and development to enable tomorrow's industries, and dealing with the mental health impacts. The book explores the potential impacts on sectors ranging from healthcare and automotive to legal and education. The implications for business itself are also examined from leadership and HR to sales and business ethics.

"In the 1970s, Japanese robotics expert Masahiro Mori published an article that coined and theorized the idea of the "uncanny valley" as a measurable correlation between the human likeness of a machine and people's comfort level with its presence. Criticized as flawed from the moment of its appearance and eventually debunked by empirical studies, Mori's original mapping of the "uncanny valley" may have no scientific grounding, but the term still endures as an apt metaphor for a technologically induced terrain of philosophical, biological, and social uncertainty. With the development of major technologies from the atom bomb to the digital computer and the emergence of cybernetics and artificial intelligence as academic disciplines since the Second World War, this terrain is no longer the sole purview of life-like automatons or robots but is increasingly occupied by developments in machine intelligence, biodigital mergence, and related issues of cloning and other forms of genetic manipulation that have reshaped the debate around the liminality of humanity. As the construction and definitions of subjectives and societies are increasingly organized and shaped by technological events that imitate or improve upon-even if only partially-fundamental functions of our bodies and minds, the question of what it means to be or remain human has been reopened for debate"--

This is an open access book. Statistical machine learning (ML) has triggered a renaissance of artificial intelligence (AI). While the most successful ML models, including Deep Neural Networks (DNN), have developed better predictivity, they have become increasingly complex, at the expense of human interpretability (correlation vs. causality). The field of explainable AI (xAI) has emerged with the goal of creating tools and models that are both predictive and interpretable and understandable for humans. Explainable AI is receiving huge interest in the machine learning and AI research communities, across academia, industry, and government, and there is now an excellent opportunity to push towards successful explainable AI applications. This volume will help the research community to accelerate this process, to promote a more systematic use of explainable AI to improve models in diverse applications, and ultimately to better understand how current explainable AI methods need to be improved and what kind of theory of explainable AI is needed. After overviews of current methods and challenges, the editors include chapters that describe new developments in explainable AI. The contributions are from leading researchers in the field, drawn from both academia and industry, and many of the chapters take a clear interdisciplinary approach to problem-solving. The concepts discussed include explainability, causability, and AI interfaces with humans, and the applications include image processing, natural language, law, fairness, and climate science.

This book proposes a regulatory system for ensuring that AI makes fair decisions. No one wants to be the subject of an unfair decision made by an AI, and fairness is so important to society that we are likely to want to regulate to demand it. But how? This book attempts to answer that question. The aim of regulation must be for an AI's decisions to match the human conception of fairness. To understand what that is, the book proposes a holistic understanding of fairness, which tells us what regulation must try to achieve. However, regulation is not an abstract activity – it regulates how humans behave, and the humans in question are those who develop and use AI for decision-making. Thus the book investigates how those humans are attempting to achieve AI fairness. It finds that there is a serious mismatch between how technologists conceptualise fairness, compared to other humans. How can AI regulation bridge this gap? Traditional models of regulation cannot solve this problem. Fairness is too nuanced, too contextual, and is ultimately a human emotional response. Instead the book proposes to place the responsibility on the AI community to explain and justify their efforts to achieve fairness, basing regulatory and legal responses on how well that explanation deals with the risks that particular AI presents, and whether the AI operates in accordance with the explanation in use. The book concludes by examining how far this regulatory model might be useful for some of the other social problems which AI generates. An original and significant contribution to the literature on AI regulation, this book is a must-read for those working in the areas of law, regulation, and technology.

This book constitutes the refereed proceedings of the 12th International Conference of the Italian Association for Artificial Intelligence, AI*IA 2011, held in Palermo, Italy, in September 2011. The 31 revised full papers presented together with 3 invited talks and 13 posters were carefully reviewed and selected from 58 submissions. The papers are organized in topical sections on machine learning; distributed AI: robotics and MAS; theoretical issues: knowledge representation and reasoning; planning, cognitive modeling; natural language processing; and AI applications.

This collection of essays by 12 members of the MIT staff, provides an inside reporton the scope and expectations of current research in one of the world's major AI centers. Thechapters on artificial intelligence, expert systems, vision, robotics, and natural language provideboth a broad overview of current areas of activity and an assessment of the field at a time of greatpublic interest and rapid technological progress.Contents: Artificial Intelligence (Patrick H.Winston and Karen Prendergast). KnowledgeBased Systems (Randall Davis). Expert-System Tools andTechniques (Peter Szolovits). Medical Diagnosis: Evolution of Systems Building Expertise (Ramesh S.Patil). Artificial Intelligence and Software Engineering (Charles Rich and Richard C. Waters).Intelligent Natural Language Processing (Robert C. Berwick). Automatic Speech Recognition andUnderstanding (Victor W. Zue). Robot Programming and Artificial Intelligence (Tomas Lozano-Perez).Robot Hands and Tactile Sensing (John M. Hollerbach). Intelligent Vision (Michael Brady). MakingRobots See (W. Eric L. Grimson). Autonomous Mobile Robots (Rodney A. Brooks).W. Eric L. Grimson,author of From Images to Surfaces: A Computational Study of the Human Early Vision System (MIT Press1981), and Ramesh S. Patil are both Assistant Professors in the Department of Electrical Engineeringand Computer Science at MIT. AI in the 1980s and Beyond is included in the Artificial IntelligenceSeries, edited by Patrick H. Winston and Michael Brady.

In today's rapidly evolving business landscape, artificial intelligence (AI) has emerged as a transformative force, revolutionizing how organizations operate, compete, and innovate. "AI in Business" is your comprehensive guide to understanding and leveraging the power of AI in the corporate world. This ebook provides a concise yet thorough exploration of the myriad ways AI is reshaping industries and driving business success. From enhancing customer experiences to optimizing operational efficiency, AI offers unparalleled opportunities for growth and innovation. Through real-world examples, case studies, and expert insights, "AI in Business" equips you with the knowledge and strategies needed to harness the full potential of AI within your organization. Discover the essential concepts of AI, explore its diverse applications across various business functions, and learn how to navigate the challenges and ethical considerations associated with its implementation. Whether you're a business leader seeking to stay ahead of the curve or a professional looking to capitalize on the AI revolution, this ebook provides actionable guidance for unlocking the competitive advantage of AI in today's dynamic marketplace. Join us on a journey into the future of business, where AI is not just a tool but a strategic imperative for success. "AI in Business" is your roadmap to navigating this exciting new frontier and driving sustainable growth in an AI-driven world.

Discover the true potential of AI beyond the hype with this insightful and thought-provoking book. From healthcare to finance, transportation to manufacturing, explore the many ways in which AI is transforming industries and society, as well as the ethical challenges that must be addressed. Written in an accessible and engaging style, this book is essential reading for anyone interested in the future of technology and its impact on our world.