Artificial Intelligence (AI) is being rapidly introduced into the workplace, creating debate around what AI means for our work and organizations. This book gives grounded counterweight to provocative newspaper headlines by using in-depth case studies of eight organizations' experiences of implementing and using AI, providing readers with a solid understanding of what is actually happening in practice. Critical yet constructive, the authors address the challenges of implementing AI: organizing for data, testing and validating, algorithmic brokering, and changing work. Using a combination of existing literature and thorough practical examples, they provide answers to questions such as: What data do I need? When is a system good enough to actually take over tasks? And how can my employees be prepared for working with AI? The book presents four recommendations for WISE management of AI, requiring work-related insights, interdisciplinary knowledge, sociotechnical change processes, and ethical awareness. Offering insight into the unique characteristics of AI in organizations, this book will be essential reading for scholars of business and management, data analytics and information systems, technology and innovation, and computer science. With practical recommendations for managing the challenges of AI, it will also provide business managers with reflections to improve their own AI development and implementation processes.

The proliferation of virtual and augmented reality technologies into society raise significant questions for judges, legal institutions, and policy makers. For example, when should activities that occur in virtual worlds, or virtual images that are projected into real space (that is, augmented reality), count as protected First Amendment 'speech'? When should they instead count as a nuisance or trespass? Under what circumstances would the copying of virtual images infringe intellectual property laws, or the output of intelligent virtual avatars be patentable inventions or works of authorship eligible for copyright? And when should a person (or computer) face legal consequences for allegedly harmful virtual acts? The Research Handbook on the Law of Virtual and Augmented Reality addresses these questions and others, drawing upon free speech doctrine, criminal law, the law of data protection and privacy, and of jurisdiction, as well as upon potential legal rights for increasingly intelligent virtual avatars in VR worlds. The Handbook offers a comprehensive look at challenges to various legal doctrines raised by the emergence - and increasing use of - virtual and augmented reality worlds, and at how existing law in the USA, Europe, and other jurisdictions might apply to these emerging technologies, or evolve to address them. It also considers what legal questions about virtual and augmented reality are likely to be important, not just for judges and legal scholars, but also for the established businesses and start-ups that wish to make use of, and help shape, these important new technologies. This comprehensive Research Handbook will be an invaluable reference to those looking to keep pace with the dynamic field of virtual and augmented reality, including students and researchers studying intellectual property law as well as legal practitioners, computer scientists, engineers, game designers, and business owners. Contributors include: W. Barfield, P.S. Berman, M.J. Blitz, S.J. Blodgett-Ford, J. Danaher, W. Erlank, J.A.T. Fairfield, J. Garon, G. Hallevy, B. Lewis, H.Y.F. Lim, C. Nwaneri, S.R. Peppet, M. Risch, A.L. Rossow, J. Russo, M. Supponen, A.M. Underhill, B.D. Wassom, A. Williams, G. Yadin

Innovations in Artificial Intelligence and Human Computer Interaction in the Digital Era investigates the interaction and growing interdependency of the HCI and AI fields, which are not usually addressed in traditional approaches. Chapters explore how well AI can interact with users based on linguistics and user-centered design processes, especially with the advances of AI and the hype around many applications. Other sections investigate how HCI and AI can mutually benefit from a closer association and the how the AI community can improve their usage of HCI methods like “Wizard of Oz” prototyping and “Thinking aloud” protocols. Moreover, HCI can further augment human capabilities using new technologies. This book demonstrates how an interdisciplinary team of HCI and AI researchers can develop extraordinary applications, such as improved education systems, smart homes, smart healthcare and map Human Computer Interaction (HCI) for a multidisciplinary field that focuses on the design of computer technology and the interaction between users and computers in different domains.

Stochastic processes have a wide range of applications ranging from image processing, neuroscience, bioinformatics, financial management, and statistics. Mathematical, physical, and engineering systems use stochastic processes for modeling and reasoning phenomena. While comparing AI-stochastic systems with other counterpart systems, we are able to understand their significance, thereby applying new techniques to obtain new real-time results and solutions. Stochastic Processes and Their Applications in Artificial Intelligence opens doors for artificial intelligence experts to use stochastic processes as an effective tool in real-world problems in computational biology, speech recognition, natural language processing, and reinforcement learning. Covering key topics such as social media, big data, and artificial intelligence models, this reference work is ideal for mathematicians, industry professionals, researchers, scholars, academicians, practitioners, instructors, and students.

Originating from papers presented at the 18th International Conference on Railway Engineering Design and Operation, this book provides up-to-date research on the use of advanced systems, promoting their general awareness throughout the management, design, manufacture and operation of railways and other emerging passenger, freight and transit systems. A key emphasis is placed on the use of computer systems in advanced railway engineering. The included works are compiled from a variety of specialists interested in the development of railways, including managers, consultants, railway engineers, designers of advanced train control systems and computer specialists. Topics covered include: Traffic safety, security and monitoring; Train and railways analysis; Operation of rail networks; Advanced train control; Energy-efficient design; Traffic modelling and simulation.

From the inventor of the PalmPilot comes a new and compelling theory of intelligence, brain function, and the future of intelligent machines
Jeff Hawkins, the man who created the PalmPilot, Treo smart phone, and other handheld devices, has reshaped our relationship to computers. Now he stands ready to revolutionize both neuroscience and computing in one stroke, with a new understanding of intelligence itself.
Hawkins develops a powerful theory of how the human brain works, explaining why computers are not intelligent and how, based on this new theory, we can finally build intelligent machines.
The brain is not a computer, but a memory system that stores experiences in a way that reflects the true structure of the world, remembering sequences of events and their nested relationships and making predictions based on those memories. It is this memory-prediction system that forms the basis of intelligence, perception, creativity, and even consciousness.
In an engaging style that will captivate audiences from the merely curious to the professional scientist, Hawkins shows how a clear understanding of how the brain works will make it possible for us to build intelligent machines, in silicon, that will exceed our human ability in surprising ways.
Written with acclaimed science writer Sandra Blakeslee, "On Intelligence" promises to completely transfigure the possibilities of the technology age. It is a landmark book in its scope and clarity.

This book proposes various deep learning models featuring how deep learning algorithms have been applied and used in real-life settings. The complexity of real-world scenarios and constraints imposed by the environment, together with budgetary and resource limitations, have posed great challenges to engineers and developers alike, to come up with solutions to meet these demands. This book presents case studies undertaken by its contributors to overcome these problems. These studies can be used as references for designers when applying deep learning in solving real-world problems in the areas of vision, signals, and networks.The contents of this book are divided into three parts. In the first part, AI vision applications in plant disease diagnostics, PM2.5 concentration estimation, surface defect detection, and ship plate identification, are featured. The second part introduces deep learning applications in signal processing; such as time series classification, broad-learning based signal modulation recognition, and graph neural network (GNN) based modulation recognition. Finally, the last section of the book reports on graph embedding applications and GNN in AI for networks; such as an end-to-end graph embedding method for dispute detection, an autonomous System-GNN architecture to infer the relationship between Apache software, a Ponzi scheme detection framework to identify and detect Ponzi schemes, and a GNN application to predict molecular biological activities.

Affective computing is a nascent field situated at the intersection of artificial intelligence with social and behavioral science. It studies how human emotions are perceived and expressed, which then informs the design of intelligent agents and systems that can either mimic this behavior to improve their intelligence or incorporate such knowledge to effectively understand and communicate with their human collaborators. Affective computing research has recently seen significant advances and is making a critical transformation from exploratory studies to real-world applications in the emerging research area known as applied affective computing. This book offers readers an overview of the state-of-the-art and emerging themes in affective computing, including a comprehensive review of the existing approaches to affective computing systems and social signal processing. It provides in-depth case studies of applied affective computing in various domains, such as social robotics and mental well-being. It also addresses ethical concerns related to affective computing and how to prevent misuse of the technology in research and applications. Further, this book identifies future directions for the field and summarizes a set of guidelines for developing next-generation affective computing systems that are effective, safe, and human-centered. For researchers and practitioners new to affective computing, this book will serve as an introduction to the field to help them in identifying new research topics or developing novel applications. For more experienced researchers and practitioners, the discussions in this book provide guidance for adopting a human-centered design and development approach to advance affective computing.

Data Ethics of Power takes a reflective and fresh look at the ethical implications of transforming everyday life and the world through the effortless, costless, and seamless accumulation of extra layers of data. By shedding light on the constant tensions that exist between ethical principles and the interests invested in this socio-technical transformation, the book bridges the theory and practice divide in the study of the power dynamics that underpin these processes of the digitalization of the world. Gry Hasselbalch expertly draws on nearly two decades of experience in the field, and key literature, to advance a better understanding of the challenges faced by big data and AI developers. She provides an innovative ethical framework for studying and governing Big-Data and Artificial Intelligence. Offering both a historical account and a theoretical analysis of power dynamics and their ethical implications, as well as incisive ideas to guide future research and governance practices, the book makes a significant contribution to the establishment of an emerging data and AI ethics discipline. This timely book is a must-read for scholars studying AI, data, and technology ethics. Policymakers in the regulatory, governance, public administration, and management sectors will find the practical proposals for a human-centric approach to big data and AI to be a valuable resource for revising and developing future policies.

This thought-provoking book challenges the way we think about the regulation of cryptoassets based on cryptographic consensus technology. Bringing a timely new perspective, Syren Johnstone critiques the application of a financial regulation narrative to cryptoassets, questions the assumptions on which it is based, and considers its impact on industry development. Providing new insights into the dynamics of oversight regulation, Johnstone argues that the financial narrative stifles the 'New Prospect' for the formation of novel commercial relationships and institutional arrangements. The book asks whether regulations developed in the 20th century remain appropriate to apply to a technology emerging in the 21st, suggesting it is time to think about how to regulate for ecosystem development. Johnstone concludes with proposals for reform, positing a new framework that facilitates industry aspirations while remaining sustainable and compatible with regulatory objectives. Rethinking the Regulation of Cryptoassets will be an invaluable read for policy makers, regulators and technologists looking for a deeper understanding of the issues surrounding cryptoasset regulation and possible alternative approaches. It will also be of interest to scholars and students researching the intersection of law, technology, regulation and finance.

Creativity has been integral to the development of the modern State, and yet it is becoming increasingly sidelined, especially as a result of the development of new machinic technologies including 3D printing. Arguing that inner creativity has been endangered by the rise of administrative regulation, James Griffin explores a number of reforms to ensure that upcoming regulations do take creativity into account. The State of Creativity examines how the State has become distanced from individual processes of creativity. This book investigates how the failure to incorporate creativity into administrative regulation is, in fact, adversely impacting the regulation of new technologies such as 3D and 4D printing and augmented reality, by focusing on issues concerning copyright and patents. This is an important read for intellectual property law scholars, as well as those studying computer science who wish to gain a more in-depth understanding of the current laws surrounding digital technologies such as 3D printing in our modern world. Legal practitioners wanting to remain abreast of developments surrounding 3D printing will also benefit from this book.

Zeroing Neural Networks Describes the theoretical and practical aspects of finite-time ZNN methods for solving an array of computational problems Zeroing Neural Networks (ZNN) have become essential tools for solving discretized sensor-driven time-varying matrix problems in engineering, control theory, and on-chip applications for robots. Building on the original ZNN model, finite-time zeroing neural networks (FTZNN) enable efficient, accurate, and predictive real-time computations. Setting up discretized FTZNN algorithms for different time-varying matrix problems requires distinct steps. Zeroing Neural Networks provides in-depth information on the finite-time convergence of ZNN models in solving computational problems. Divided into eight parts, this comprehensive resource covers modeling methods, theoretical analysis, computer simulations, nonlinear activation functions, and more. Each part focuses on a specific type of time-varying computational problem, such as the application of FTZNN to the Lyapunov equation, linear matrix equation, and matrix inversion. Throughout the book, tables explain the performance of different models, while numerous illustrative examples clarify the advantages of each FTZNN method. In addition, the book: Describes how to design, analyze, and apply FTZNN models for solving computational problems Presents multiple FTZNN models for solving time-varying computational problems Details the noise-tolerance of FTZNN models to maximize the adaptability of FTZNN models to complex environments Includes an introduction, problem description, design scheme, theoretical analysis, illustrative verification, application, and summary in every chapter Zeroing Neural Networks: Finite-time Convergence Design, Analysis and Applications is an essential resource for scientists, researchers, academic lecturers, and postgraduates in the field, as well as a valuable reference for engineers and other practitioners working in neurocomputing and intelligent control.