Artificial Intelligence for Sustainable Value Creation provides a detailed and insightful exploration of both the possibilities and the challenges that accompany widespread Artificial Intelligence. Providing a cutting edge analysis of the impact of AI in business and society, the editors offer an opportunity to assess what is known about managing other forms of information systems, strategy, and marketing, and to re-examine this knowledge in situations involving AI. This comprehensive book explores how human- centric AI systems create value inside organizations, distinguishing three main components: ethical value, societal value, and business value. Using a multidisciplinary perspective, this discerning book addresses the interests of a wide spectrum of practitioners, students, and researchers alike who are interested in identifying the value generated by AI systems in management.

How robots will change our world Some fear that robots could do half our jobs and even wipe us out. But is that likely? Smart machines already make our cars and clean our homes. Soon they could drive us about, teach our children, and keep our parents company. While dealing with the ethical concerns about Artificial Intelligence, Bennie Mols and Nieske Vergunst reveal the history, present and future of robots. They show how moving AI could allow the lame to walk again, rescue survivors from collapsed buildings, and boost the global fight against hunger and pollution. Welcome to a vivid view of our robot future. With 60 colour photos. Topics From dolls to industrial workers, a history of robots How robots respond to their surroundings What robots learn about human speech Why self-driving cars are safer and greener The possibilities of robots in education Meet the 'cyborgs' who learn to walk again Why evolution designs the best robots Will rogue robots take over the world? Using robots as weapons and drones What the future holds: 2100, a Robot Odyssey Table of Contents 1 A short history of robots, from dolls to androids Machines as man throughout history Mechanical dolls: forerunners of the robot Enter the working humanoid robots The next step: android robots that look like you Uncanny valley: the problem with creepy robots 2. How do robots see their surroundings? Getting to grips with a new environment Seeing through the eyes of a robot Training robots to recognise objects Robots can see what a person cannot see Feeling with whiskers: sensing the way forward Robots use electronic ears to listen 3. How does a robot brain work? A robot must learn to think like a human Keeping it simple with an insect brain Machine learning is trial and error Robots can learn without supervision The football world cup for robots Developing robot emotional intelligence 4. Giving humans a helping hand Robots suck: doing the dirty jobs at home A robotic arm reaches deep into the supply chain Joseph Engelberger, father of car factory robots Co-bots will work alongside people Coping with variation is Amazon's challenge Building a robot car 5. Learning to speak to people The problem with machine talk SHRDLU! The first experiment in robot conversation Toilets are hidden: translation problems A robotic teacher never runs out of patience 6. Robots get emotional Emotional robots encourage humans to interact with them A robot can work out how you are feeling Why am I afraid? Understanding human emotions Help! My robot looks angry Establishing a bond with a robot 7. Humans need robots and robots need humans Meet the robot psychologists Under-promise and over-deliver performance Silicon Valley utopias vs calm technology What is the best ratio of robots to humans? In the rubble: the search and rescue robot The paradox of robotization 8. Humans need robots and robots need humans Meet the robot psychologists Under-promise and over-deliver performance * Silicon Valley utopias vs calm technology What is the best ratio of robots to humans? In the rubble: the search and rescue robot The paradox of robotization 9. Evolution designs the best robots How robots travel in a bumpy world Robothand has nature's grip A two-legged walking robot The first robot baby Working out the best path through evolution 10. Swarming robots show the wisdom of crowds The power of robots working together A robot swarm without a boss Goal is mapping a building about to collapse Predicting how a robot will behave Robot swarms in the real world A robotic swarm looks for a queen 11. The importance of building ethical robots Isaac Asimov's three rules about rogue robots When robots go wrong Responsible roboticists are planning for the future Robots and the UN's development goals How will robots change the human race? Killing machines: robots in the military 12. 2100 - A Robot Odyssey The future of work in a robotic world Fusing mind and body with soft robotics And then the smart robot became creative Was that move really creative? Will robots really take over the world?

This incisive book provides a much-needed examination of the legal issues arising from the data economy, particularly in the light of the expanding role of algorithms and artificial intelligence in business and industry. In doing so, it discusses the pressing question of how to strike a balance in the law between the interests of a variety of stakeholders, such as AI industry, businesses and consumers. Investigating issues at the intersection of trade secrets and personal data as well as the potential legal conflicts to which this can give rise, Gintare Surblyte-Namaviciene examines what kinds of changes to the legal framework the growing data economy may require. Through an analysis of the way in which EU competition law may tackle algorithm-related problems the book also identifies a regulatory gap in the case of algorithmic manipulation in the business-to-consumer relationship. The book further argues that control by public bodies over terms and conditions often used in the data economy may be necessary for the sake of consumer protection. Scholars in competition law and regulatory governance, particularly those with an interest in the impacts of technology, will find this to be critical reading. It will also be beneficial to practitioners and policy makers working at the intersections of regulation and technology.

Written chemical formulas, such as C2H6O, can tell us the constituent atoms a molecule contains but they cannot differentiate between the possible geometrical arrangements (isomers) of these models. Yet the chemical properties of different isomers can vary hugely. Therefore, to understand the world of chemistry we need to ask what kind of isomers can be produced from a given atomic composition, how are isomers converted into each other, how do they decompose into smaller pieces, and how can they be made from smaller pieces? The answers to these questions will help us to discover new chemistry and new molecules. A potential energy surface (PES) describes a system, such as a molecule, based on geometrical parameters. The mathematical properties of the PES can be used to calculate probable isomer structures as well as how they are formed and how they might behave. Exploration on Quantum Chemical Potential Energy Surfaces focuses on the PES search based on quantum chemical calculations. It describes how to explore the chemical world on PES, discusses fundamental methods and specific techniques developed for efficient exploration on PES, and demonstrates several examples of the PES search for chemical structures and reaction routes.

The promises and realities of digital innovation have come to suffuse everything from city regions to astronomy, government to finance, art to medicine, politics to warfare, and from genetics to reality itself. Digital systems augmenting physical space, buildings, and communities occupy a special place in the evolutionary discourse about advanced technology. The two Intelligent Environments books edited by Peter Droege span a quarter of a century across this genre. The second volume, Intelligent Environments: Advanced Systems for a Healthy Planet, asks: how does civilization approach thinking systems, intelligent spatial models, design methods, and support structures designed for sustainability, in ways that could counteract challenges to terrestrial habitability? This book examines a range of baseline and benchmark practices but also unusual and even sublime endeavors across regions, currencies, infrastructure, architecture, transactive electricity, geodesign, net-positive planning, remote work, integrated transport, and artificial intelligence in understanding the most immediate spatial setting: the human body. The result of this quest is both highly informative and useful, but also critical. It opens windows on what must fast become a central and overarching existential focus in the face of anthropogenic planetary heating and other threats-and raises concomitant questions about direction, scope, and speed of that change.

Cardiovascular and Coronary Artery Imaging, Volume Two presents the basics of echocardiography, nuclear imaging and magnetic resonance imaging (MRI) and provides insights into their appropriate use. The book covers state-of-the-art approaches for automated non-invasive systems for early cardiovascular and coronary artery disease diagnosis. It includes several prominent imaging modalities such as MRI, CT and PET technologies. Other sections focus on major trends and challenges in this area and present the latest techniques for cardiovascular and coronary image analysis.

Coulomb Interactions in Particle Beams, Volume 223 in the Advances in Imaging and Electron Physics series, merges two long-running serials, Advances in Electronics and Electron Physics and Advances in Optical and Electron Microscopy. The series features articles on the physics of electron devices (especially semiconductor devices), particle optics at high and low energies, microlithography, image science, digital image processing, electromagnetic wave propagation, electron microscopy, and computing methods used in all these domains, with this release exploring Coulomb Interactions in Particle Beams.

Statistical Modeling in Machine Learning: Concepts and Applications presents the basic concepts and roles of statistics, exploratory data analysis and machine learning. The various aspects of Machine Learning are discussed along with basics of statistics. Concepts are presented with simple examples and graphical representation for better understanding of techniques. This book takes a holistic approach - putting key concepts together with an in-depth treatise on multi-disciplinary applications of machine learning. New case studies and research problem statements are discussed, which will help researchers in their application areas based on the concepts of statistics and machine learning. Statistical Modeling in Machine Learning: Concepts and Applications will help statisticians, machine learning practitioners and programmers solving various tasks such as classification, regression, clustering, forecasting, recommending and more.

Data Analysis for Social Microblogging Platforms explores the nature of microblog datasets, also covering the larger field which focuses on information, data and knowledge in the context of natural language processing. The book investigates a range of significant computational techniques which enable data and computer scientists to recognize patterns in these vast datasets, including machine learning, data mining algorithms, rough set and fuzzy set theory, evolutionary computations, combinatorial pattern matching, clustering, summarization and classification. Chapters focus on basic online micro blogging data analysis research methodologies, community detection, summarization application development, performance evaluation and their applications in big data.

Elgar Advanced Introductions are stimulating and thoughtful introductions to major fields in the social sciences and law, expertly written by the world's leading scholars. Designed to be accessible yet rigorous, they offer concise and lucid surveys of the substantive and policy issues associated with discrete subject areas. Woodrow Barfield and Ugo Pagallo present a succinct introduction to the legal issues related to the design and use of artificial intelligence (AI). Exploring human rights, constitutional law, data protection, criminal law, tort law, and intellectual property law, they consider the laws of a number of jurisdictions including the US, the European Union, Japan, and China, making reference to case law and statutes. Key features include: a critical insight into human rights and constitutional law issues which may be affected by the use of AI discussion of the concept of legal personhood and how the law might respond as AI evolves in intelligence an introduction to current laws and statutes which apply to AI and an identification of the areas where future challenges to the law may arise. This Advanced Introduction is ideal for law and social science students with an interest in how the law applies to AI. It also provides a useful entry point for legal practitioners seeking an understanding of this emerging field.

Applying mechanisms and principles of human intelligence and converging the brain and artificial intelligence (AI) is currently a research trend. The applications of AI in brain simulation are countless. Brain-inspired intelligent systems will improve next-generation information processing by applying theories, techniques, and applications inspired by the information processing principles from the brain. Exploring Future Opportunities of Brain-Inspired Artificial Intelligence focuses on the convergence of AI with brain-inspired intelligence. It presents research on brain-inspired cognitive machines with vision, audition, language processing, and thinking capabilities. Covering topics such as data analysis tools, knowledge representation, and super-resolution, this premier reference source is an essential resource for engineers, developers, computer scientists, students and educators of higher education, librarians, researchers, and academicians.

In healthcare, a digital twin is a digital representation of a patient or healthcare system using integrated simulations and service data. The digital twin tracks a patient's records, crosschecks them against registered patterns and analyses any diseases or contra indications. The digital twin uses adaptive analytics and algorithms to produce accurate prognoses and suggest appropriate interventions. A digital twin can run various medical scenarios before treatment is initiated on the patient, thus increasing patient safety as well as providing the most appropriate treatments to meet the patient's requirements. Digital Twin Technologies for Healthcare 4.0 discusses how the concept of the digital twin can be merged with other technologies, such as artificial intelligence (AI), machine learning (ML), big data analytics, IoT and cloud data management, for the improvement of healthcare systems and processes. The book also focuses on the various research perspectives and challenges in implementation of digital twin technology in terms of data analysis, cloud management and data privacy issues. With chapters on visualisation techniques, prognostics and health management, this book is a must-have for researchers, engineers and IT professionals in healthcare as well as those involved in using digital twin technology, AI, IoT & big data analytics for novel applications.