The hidden costs of artificial intelligence—from natural resources and labor to privacy, equality, and freedom.

What happens when artificial intelligence saturates political life and depletes the planet? How is AI shaping our understanding of ourselves and our societies? Drawing on more than a decade of research, award‑winning scholar Kate Crawford reveals how AI is a technology of extraction: from the minerals drawn from the earth to the labor pulled from low-wage information workers to the data taken from every action and expression.

Crawford reveals how this planetary network is fueling a shift toward undemocratic governance and increased inequity. Rather than taking a narrow focus on code and algorithms, Crawford offers us a material and political perspective on what it takes to make AI and how it centralizes power. This is an urgent account of what is at stake as technology companies use artificial intelligence to reshape the world.

This volume provides an extensive overview of the Ethics of Artificial Intelligence for the Sustainable Development Goals. The authors are experts contributing with perspectives from different fields. The comprehensive collection of chapters illustrates the pressing governance problems related to using AI for the SDGs, and case studies describing how AI is advancing and can advance the achievement of the Goals. Students, scholars, and practitioners working on AI for SDGs, the ethical governance of AI, sustainability, and the fourth revolution can find this book a helpful reference.

The topics covered in this book range from modeling and programming languages and environments, via approaches for design and verification, to issues of ethics and regulation. In terms of techniques, there are results on model-based engineering, product lines, mission specification, component-based development, simulation, testing, and proof. Applications range from manufacturing to service robots, to autonomous vehicles, and even robots than evolve in the real world. A final chapter summarizes issues on ethics and regulation based on discussions from a panel of experts. The origin of this book is a two-day event, entitled RoboSoft, that took place in November 2019, in London. Organized with the generous support of the Royal Academy of Engineering and the University of York, UK, RoboSoft brought together more than 100 scientists, engineers and practitioners from all over the world, representing 70 international institutions. The intended readership includes researchers and practitioners with all levels of experience interested in working in the area of robotics, and software engineering more generally. The chapters are all self-contained, include explanations of the core concepts, and finish with a discussion of directions for further work. Chapters 'Towards Autonomous Robot Evolution', 'Composition, Separation of Roles and Model-Driven Approaches as Enabler of a Robotics Software Ecosystem' and 'Verifiable Autonomy and Responsible Robotics' are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

This present book includes a set of selected revised and extended versions of the best papers presented at the 11th International Joint Conference on Computational Intelligence (IJCCI 2019) - held in Vienna, Austria, from 17 to 19 September 2019. The authors focus on three outstanding fields of Computational Intelligence through the selected panel, namely Evolutionary Computation, Fuzzy Computation and Neural Computation. Besides presenting the recent advances of the selected areas, the book aims to aggregate new and innovative solutions for confirmed researchers and, on the other hand, to provide a source of information and/or inspiration for young interested researchers or learners in the ever-expanding and current filed of Computational Intelligence. It constitutes a precious provision of knowledge for individual researchers as well as represents a valuable sustenance for collective use in academic libraries (of universities and engineering schools) relating innovative techniques in various fields of applications.

This book describes methods for statistical brain imaging data analysis from both the perspective of methodology and from the standpoint of application for software implementation in neuroscience research. These include those both commonly used (traditional established) and state of the art methods. The former is easier to do due to the availability of appropriate software. To understand the methods it is necessary to have some mathematical knowledge which is explained in the book with the help of figures and descriptions of the theory behind the software. In addition, the book includes numerical examples to guide readers on the working of existing popular software. The use of mathematics is reduced and simplified for non-experts using established methods, which also helps in avoiding mistakes in application and interpretation. Finally, the book enables the reader to understand and conceptualize the overall flow of brain imaging data analysis, particularly for statisticians and data-scientists unfamiliar with this area. The state of the art method described in the book has a multivariate approach developed by the authors' team. Since brain imaging data, generally, has a highly correlated and complex structure with large amounts of data, categorized into big data, the multivariate approach can be used as dimension reduction by following the application of statistical methods. The R package for most of the methods described is provided in the book. Understanding the background theory is helpful in implementing the software for original and creative applications and for an unbiased interpretation of the output. The book also explains new methods in a conceptual manner. These methodologies and packages are commonly applied in life science data analysis. Advanced methods to obtain novel insights are introduced, thereby encouraging the development of new methods and applications for research into medicine as a neuroscience.

This volume explores how context has been and can be used in computing to model human behaviors, actions and communications as well as to manage data and knowledge. It addresses context management and exploitation of context for sharing experience across domains. The book serves as a user-centric guide for readers wishing to develop context-based applications, as well as an intellectual reference on the concept of context. It provides a broad yet deep treatment of context in computing and related areas that depend heavily on computing. The coverage is broad because of its cross-disciplinary nature but treats topics at a sufficient depth to permit a reader to implement context in his/her computational endeavors. The volume addresses how context can be integrated in software and systems and how it can be used in a computing environment. Furthermore, the use of context to represent the human dimension, individually as well as collectively is explained. Contributions also include descriptions of how context has been represented in formal as well as non-formal, structured approaches. The last section describes several human behavior representation paradigms based on the concept of context as its central representational element. The depth and breadth of this content is certain to provide useful as well as intellectually enriching information to readers of diverse backgrounds who have an interest in or are intrigued by using context to assist in their representation of the real world.

This book deals with the stabilization issue of infinite dimensional dynamical systems both at the theoretical and applications levels. Systems theory is a branch of applied mathematics, which is interdisciplinary and develops activities in fundamental research which are at the frontier of mathematics, automation and engineering sciences. It is everywhere, innumerable and daily, and moreover is there something which is not system: it is present in medicine, commerce, economy, psychology, biological sciences, finance, architecture (construction of towers, bridges, etc.), weather forecast, robotics, automobile, aeronautics, localization systems and so on. These are the few fields of application that are useful and even essential to our society. It is a question of studying the behavior of systems and acting on their evolution. Among the most important notions in system theory, which has attracted the most attention, is stability. The existing literature on systems stability is quite important, but disparate, and the purpose of this book is to bring together in one document the essential results on the stability of infinite dimensional dynamical systems. In addition, as such systems evolve in time and space, explorations and research on their stability have been mainly focused on the whole domain in which the system evolved. The authors have strongly felt that, in this sense, important considerations are missing: those which consist in considering that the system of interest may be unstable on the whole domain, but stable in a certain region of the whole domain. This is the case in many applications ranging from engineering sciences to living science. For this reason, the authors have dedicated this book to extension of classical results on stability to the regional case. This book considers a very important issue, which is that it should be accessible to mathematicians and to graduate engineering with a minimal background in functional analysis. Moreover, for the majority of the students, this would be their only acquaintance with infinite dimensional system. Accordingly, it is organized by following increasing difficulty order. The two first chapters deal with stability and stabilization of infinite dimensional linear systems described by partial differential equations. The following chapters concern original and innovative aspects of stability and stabilization of certain classes of systems motivated by real applications, that is to say bilinear and semi-linear systems. The stability of these systems has been considered from a global and regional point of view. A particular aspect concerning the stability of the gradient has also been considered for various classes of systems. This book is aimed at students of doctoral and master's degrees, engineering students and researchers interested in the stability of infinite dimensional dynamical systems, in various aspects.

This book describes concepts and tools needed for water resources management, including methods for modeling, simulation, optimization, big data analysis, data mining, remote sensing, geographical information system, game theory, conflict resolution, System dynamics, agent-based models, multiobjective, multicriteria, and multiattribute decision making and risk and uncertainty analysis, for better and sustainable management of water resources and consumption, thus mitigating the present and future global water shortage crisis. It presents the applications of these tools through case studies which demonstrate its benefits of proper management of water resources systems. This book acts as a reference for students, professors, industrial practitioners, and stakeholders in the field of water resources and hydrology.

This provocative book investigates the relationship between law and artificial intelligence (AI) governance, and the need for new and innovative approaches to regulating AI and big data in ways that go beyond market concerns alone and look to sustainability and social good. Taking a multidisciplinary approach, the contributors demonstrate the interplay between various research methods, and policy motivations, to show that law-based regulation and governance of AI is vital to efforts at ensuring justice, trust in administrative and contractual processes, and inclusive social cohesion in our increasingly technologically-driven societies. The book provides valuable insights on the new challenges posed by a rapid reliance on AI and big data, from data protection regimes around sensitive personal data, to blockchain and smart contracts, platform data reuse, IP rights and limitations, and many other crucial concerns for law's interventions. The book also engages with concerns about the 'surveillance society', for example regarding contact tracing technology used during the Covid-19 pandemic. The analytical approach provided will make this an excellent resource for scholars and educators, legal practitioners (from constitutional law to contract law) and policy makers within regulation and governance. The empirical case studies will also be of great interest to scholars of technology law and public policy. The regulatory community will find this collection offers an influential case for law's relevance in giving institutional enforceability to ethics and principled design.

This book presents Proceedings of the International Conference on Intelligent Systems and Networks (ICISN 2021), held at Hanoi in Vietnam. It includes peer-reviewed high-quality articles on intelligent system and networks. It brings together professionals and researchers in the area and presents a platform for exchange of ideas and to foster future collaboration. The topics covered in this book include-foundations of computer science; computational intelligence language and speech processing; software engineering software development methods; wireless communications signal processing for communications; electronics track IoT and sensor systems embedded systems; etc.

This book discusses the various open issues of blockchain technology, such as the efficiency of blockchain in different domains of digital cryptocurrency, smart contracts, smart education system, smart cities, cloud identity and access, safeguard to cybersecurity and health care. For the first time in human history, people across the world can trust each other and transact over a large peer-to-peer networks without any central authority. This proves that, trust can be built not only by centralized institution but also by protocols and cryptographic mechanisms. The potential and collaboration between organizations and individuals within peer networks make it possible to potentially move to a global collaborative network without centralization. Blockchain is a complex social, economic and technological phenomenon. This questions what the established terminologies of the modern world like currency, trust, economics and exchange would mean. To make any sense, one needs to realize how much insightful and potential it is in the context and the way it is technically developed. Due to rapid changes in accessing the documents through online transactions and transferring the currency online, many previously used methods are proving insufficient and not secure to solve the problem which arises in the safe and hassle-free transaction. Nowadays, the world changes rapidly, and a transition flow is also seen in Business Process Management (BPM). The traditional Business Process Management holds good establishment last one to two decades, but, the internal workflow confined in a single organization. They do not manage the workflow process and information across organizations. If they do so, again fall in the same trap as the control transfers to the third party that is centralized server and it leads to tampering the data, and single point of failure. To address these issues, this book highlights a number of unique problems and effective solutions that reflects the state-of-the art in blockchain Technology. This book explores new experiments and yields promising solutions to the current challenges of blockchain technology. This book is intended for the researchers, academicians, faculties, scientists, blockchain specialists, business management and software industry professionals who will find it beneficial for their research work and set new ideas in the field of blockchain. This book caters research work in many fields of blockchain engineering, and it provides an in-depth knowledge of the fields covered.

This book draws inspiration from natural shepherding, whereby a farmer utilizes sheepdogs to herd sheep, to inspire a scalable and inherently human friendly approach to swarm control. The book discusses advanced artificial intelligence (AI) approaches needed to design smart robotic shepherding agents capable of controlling biological swarms or robotic swarms of unmanned vehicles. These smart shepherding agents are described with the techniques applicable to the control of Unmanned X Vehicles (UxVs) including air (unmanned aerial vehicles or UAVs), ground (unmanned ground vehicles or UGVs), underwater (unmanned underwater vehicles or UUVs), and on the surface of water (unmanned surface vehicles or USVs). This book proposes how smart 'shepherds' could be designed and used to guide a swarm of UxVs to achieve a goal while ameliorating typical communication bandwidth issues that arise in the control of multi agent systems. The book covers a wide range of topics ranging from the design of deep reinforcement learning models for shepherding a swarm, transparency in swarm guidance, and ontology-guided learning, to the design of smart swarm guidance methods for shepherding with UGVs and UAVs. The book extends the discussion to human-swarm teaming by looking into the real-time analysis of human data during human-swarm interaction, the concept of trust for human-swarm teaming, and the design of activity recognition systems for shepherding. Presents a comprehensive look at human-swarm teaming; Tackles artificial intelligence techniques for swarm guidance; Provides artificial intelligence techniques for real-time human performance analysis.

This book extends the work from introduction of ubiquitous computing, to the Internet of things to security and to privacy aspects of ubiquitous computing. The uniqueness of this book is the combination of important fields like the Internet of things and ubiquitous computing. It assumes that the readers' goal is to achieve a complete understanding of IoT, smart computing, security issues, challenges and possible solutions. It is not oriented towards any specific use cases and security issues; privacy threats in ubiquitous computing problems are discussed across various domains. This book is motivating to address privacy threats in new inventions for a wide range of stakeholders like layman to educated users, villages to metros and national to global levels. This book contains numerous examples, case studies, technical descriptions, scenarios, procedures, algorithms and protocols. The main endeavour of this book is threat analysis and activity modelling of attacks in order to give an actual view of the ubiquitous computing applications. The unique approach will help readers for a better understanding.

This book projects a futuristic scenario that is more existent than they have been at any time earlier. To be conscious of the bursting prospective of IoT, it has to be amalgamated with AI technologies. Predictive and advanced analysis can be made based on the data collected, discovered and analyzed. To achieve all these compatibility, complexity, legal and ethical issues arise due to automation of connected components and gadgets of widespread companies across the globe. While these are a few examples of issues, the authors' intention in editing this book is to offer concepts of integrating AI with IoT in a precise and clear manner to the research community. In editing this book, the authors' attempt is to provide novel advances and applications to address the challenge of continually discovering patterns for IoT by covering various aspects of implementing AI techniques to make IoT solutions smarter. The only way to remain pace with this data generated by the IoT and acquire the concealed acquaintance it encloses is to employ AI as the eventual catalyst for IoT. IoT together with AI is more than an inclination or existence; it will develop into a paradigm. It helps those researchers who have an interest in this field to keep insight into different concepts and their importance for applications in real life. This has been done to make the edited book more flexible and to stimulate further interest in topics. All these motivated the authors toward integrating AI in achieving smarter IoT. The authors believe that their effort can make this collection interesting and highly attract the student pursuing pre-research, research and even master in multidisciplinary domain.

This book is devoted to the leading research in applying learning automaton (LA) and heuristics for solving benchmark and real-world optimization problems. The ever-increasing application of the LA as a promising reinforcement learning technique in artificial intelligence makes it necessary to provide scholars, scientists, and engineers with a practical discussion on LA solutions for optimization. The book starts with a brief introduction to LA models for optimization. Afterward, the research areas related to LA and optimization are addressed as bibliometric network analysis. Then, LA's application in behavior control in evolutionary computation, and memetic models of object migration automata and cellular learning automata for solving NP hard problems are considered. Next, an overview of multi-population methods for DOPs, LA's application in dynamic optimization problems (DOPs), and the function evaluation management in evolutionary multi-population for DOPs are discussed. Highlighted benefits * Presents the latest advances in learning automata-based optimization approaches. * Addresses the memetic models of learning automata for solving NP-hard problems. * Discusses the application of learning automata for behavior control in evolutionary computation in detail. * Gives the fundamental principles and analyses of the different concepts associated with multi-population methods for dynamic optimization problems.

This book presents the proceedings of the 2nd International Conference on Networks and Advances in Computational Technologies (NetACT19) which took place on July 23-25, 2019 at Mar Baselios College of Engineering and Technology in Thiruvananthapuram, India. The conference was in association with Bowie State University, USA, Gannon University, USA and Malardalen University, Sweden. Papers presented were included in technical programs that were part of five parallel tracks, namely Computer Application, Image Processing, Network Security, Hardware & Network Systems and Machine Learning. The proceedings brings together experts from industry, governments and academia from around the world with vast experiences in design, engineering and research. Presents the proceedings of the 2nd International Conference on Networks and Advances in Computational Technologies (NetACT19); Includes research in Computer Application, Image Processing, Network Security, Hardware & Network Systems and Machine Learning; Provides perspectives from industry, academia and government.

This book presents a collection of recent research on topics related to Pythagorean fuzzy set, dealing with dynamic and complex decision-making problems. It discusses a wide range of theoretical and practical information to the latest research on Pythagorean fuzzy sets, allowing readers to gain an extensive understanding of both fundamentals and applications. It aims at solving various decision-making problems such as medical diagnosis, pattern recognition, construction problems, technology selection, and more, under the Pythagorean fuzzy environment, making it of much value to students, researchers, and professionals associated with the field.

Immersive technology as an umbrella concept consists of multiple emerging technologies including augmented reality (AR), virtual reality (VR), gaming, simulation, and 3D printing. Research has shown immersive technology provides unique learning opportunities for experiential learning, multiple perspectives, and knowledge transfer. Due to its role in influencing learners' cognitive and affective processes, it is shown to have great potential in changing the educational landscape in the decades to come. However, there is a lack of general cognitive and affective theoretical framework to guide the diverse aspects of immersive technology research. In fact, lacking the cognitive and affective theoretical framework has begun to hamper the design and application of immersive technology in schools and related professional training. Cognitive and Affective Perspectives on Immersive Technology in Education is an essential research book that explores methods and implications for the design and implementation of upcoming immersive technologies in pedagogical and professional development settings. The book includes case studies that highlight the cognitive and affective processes in immersive technology as well as the successful applications of immersive technology in education. Featuring a wide range of topics such as curriculum design, K-12 education, and mobile learning, this book is ideal for academicians, educators, policymakers, curriculum developers, instructional designers, administrators, researchers, and students.

This book brings together papers presented at The 2nd International Conference on Artificial Intelligence in China (ChinaAI) 2020, which provides a venue to disseminate the latest developments and to discuss the interactions and links between these multidisciplinary fields. Spanning topics covering all topics in artificial intelligence with new development in China, this book is aimed at undergraduate and graduate students in Electrical Engineering, Computer Science and Mathematics, researchers and engineers from academia and industry as well as government employees (such as NSF, DOD and DOE).

As humans interact more often and more intimately with computers, and as computational systems become an ever more important element of our society, playing roles in education, the production of culture and goods, and management, it is inevitable that we should seek to interact with these systems in ways that take advantage of our powerful emotional capabilities. Creating Synthetic Emotions through Technological and Robotic Advancements compiles progressive research in the emerging and groundbreaking fields of artificial emotions, affective computing, and sociable robotics that allow humans to begin the once impossible-seeming task of interacting with robots, systems, devices, and agents. This landmark volume brings together expert international researchers to expound upon these topics as synthetic emotions move toward becoming a daily reality.

This book, to reflect the system's diverse, relevant characteristics, uses three different mathematical tools, namely probability theory, fuzzy theory and random fuzzy theory, to model and analyze the reliability of each system. Reliability system engineering is an interdisciplinary area that chiefly focuses on the lifecycle characteristics of products and involves many fields of basic mathematics, technical science and management science. In recent years, there have been many books on reliability theory, but comparatively few on the reliability of mathematical models, or the reliability of mathematical models based on single probability theory or fuzzy theory. The findings presented here will not only enrich and expand traditional reliability theory, but also promote the development of related disciplines, lending the book considerable theoretical significance.

This book discusses biologically inspired robotic actuators designed to offer improved robot performance and approaching human-like efficiency and versatility. It assesses biological actuation and control in the human motor system, presents a range of technical actuation approaches, and discusses potential applications in wearable robots, i.e., powered prostheses and exoskeletons. Gathering the findings of internationally respected researchers from various fields, the book provides a uniquely broad perspective on bioinspired actuator designs for robotics. Its scope includes fundamental aspects of biomechanics and neuromechanics, actuator and control design, and their application in (wearable) robotics. The book offers PhD students and advanced graduate students an essential introduction to the field, while providing researchers a cutting-edge research perspective.