The advancement in FinTech especially artificial intelligence (AI) and machine learning (ML), has significantly affected the way financial services are offered and adopted today. Important financial decisions such as investment decision making, macroeconomic analysis, and credit evaluation are getting more complex in the field of finance. ML is used in many financial companies which are making a significant impact on financial services. With the increasing complexity of financial transaction processes, ML can reduce operational costs through process automation which can automate repetitive tasks and increase productivity. Among others, ML can analyze large volumes of historical data and make better trading decisions to increase revenue. This book provides an exhaustive overview of the roles of AI and ML algorithms in financial sectors with special reference to complex financial applications such as financial risk management in a big data environment. In addition, it provides a collection of high-quality research works that address broad challenges in both theoretical and application aspects of AI in the field of finance.

A Wall Street Journal Bestseller 'IT SHOULD BE READ BY ANYONE TRYING TO MAKE SENSE OF GEOPOLITICS TODAY' FINANCIAL TIMES Three of our most accomplished and deep thinkers come together to explore Artificial Intelligence (AI) and the way it is transforming human society - and what it means for us all. An AI learned to win chess by making moves human grand masters had never conceived. Another AI discovered a new antibiotic by analysing molecular properties human scientists did not understand. Now, AI-powered jets are defeating experienced human pilots in simulated dogfights. AI is coming online in searching, streaming, medicine, education, and many other fields and, in so doing, transforming how humans are experiencing reality. In The Age of AI, three leading thinkers have come together to consider how AI will change our relationships with knowledge, politics, and the societies in which we live. The Age of AI is an essential roadmap to our present and our future, an era unlike any that has come before.

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.

The comprehensive compendium furnishes a quick and efficient entry point to many multiresolution techniques and facilitates the transition from an idea into a real project. It focuses on methods combining several soft computing techniques (fuzzy logic, neural networks, genetic algorithms) in a multiresolution framework.Illustrated with numerous vivid examples, this useful volume gives the reader the necessary theoretical background to decide which methods suit his/her needs.New materials and applications for multiresolution analysis are added, including notable research topics such as deep learning, graphs, and network analysis.

The Handbook on Socially Interactive Agents provides a comprehensive overview of the research fields of Embodied Conversational Agents Intelligent Virtual Agents and Social Robotics. Socially Interactive Agents (SIAs) whether virtually or physically embodied are autonomous agents that are able to perceive an environment including people or other agents reason decide how to interact and express attitudes such as emotions engagement or empathy. They are capable of interacting with people and one another in a socially intelligent manner using multimodal communicative behaviors with the goal to support humans in various domains.Written by international experts in their respective fields the book summarizes research in the many important research communities pertinent for SIAs while discussing current challenges and future directions. The handbook provides easy access to modeling and studying SIAs for researchers and students and aims at further bridging the gap between the research communities involved. In two volumes the book clearly structures the vast body of research. The first volume starts by introducing what is involved in SIAs research in particular research methodologies and ethical implications of developing SIAs. It further examines research on appearance and behavior focusing on multimodality. Finally social cognition for SIAs is investigated using different theoretical models and phenomena such as theory of mind or pro-sociality. The second volume starts with perspectives on interaction examined from different angles such as interaction in social space group interaction or long-term interaction. It also includes an extensive overview summarizing research and systems of human-agent platforms and of some of the major application areas of SIAs such as education aging support autism and games.

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?

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.

This timely book presents a detailed analysis of the role of law and regulation in the utilisation of Artificial Intelligence (AI) in the media sector. As well as contributing to the wider discussion on law and AI, the book also digs deeper by exploring pressing issues at the intersections of AI, media, and the law. Chapters critically re-examine various rights and responsibilities from the perspectives of incentives for accountable utilisation of AI in the industry. Featuring chapters from leading scholars in the field, Artificial Intelligence and the Media provides a timely and in-depth research-based contribution to complex themes - especially at the interface of new technology (including AI) with media and regulation. Analysing both legislative and ethical solutions, chapters explore what "AI" and "accountability" mean in terms of media practices, principles, and power relations, as well as how to address the AI revolution with informed law and policy in order to incentivise accountable utilisation of AI and to reduce negative societal impacts. Offering ideas for further research in the area, this book is key reading for academics and researchers in the fields of information and media law, regulation, and technology law. It may also interest media law practitioners, with research-based guidance for everyday practices and tools to prepare for future developments in the area.

In the implementation of smart cities, sensors and actuators that produce and consume enormous amounts of data in a variety of formats and ontologies will be incorporated into the system as a whole. The data produced by the participating devices need to be adequately categorized and connected to reduce duplication and conflicts. Newer edge computing techniques are needed to manage enormous amounts of data quickly and avoid overloading the cloud infrastructure. Cyber-Physical System Solutions for Smart Cities considers the most recent developments in several crucial software services and cyber infrastructures that are important to smart cities. Covering key topics such as artificial intelligence, smart data, big data, and computer science, this premier reference source is ideal for industry professionals, government officials, policymakers, scholars, researchers, academicians, instructors, and students.

Explainable artificial intelligence is proficient in operating and analyzing the unconstrainted environment in fields like robotic medicine, robotic treatment, and robotic surgery, which rely on computational vision for analyzing complex situations. Explainable artificial intelligence is a well-structured customizable technology that makes it possible to generate promising unbiased outcomes. The model's adaptability facilitates the management of heterogeneous healthcare data and the visualization of biological structures through virtual reality. Explainable artificial intelligence has newfound applications in the healthcare industry, such as clinical trial matching, continuous healthcare monitoring, probabilistic evolutions, and evidence-based mechanisms. Principles and Methods of Explainable Artificial Intelligence in Healthcare discusses explainable artificial intelligence and its applications in healthcare, providing a broad overview of state-of-the-art approaches for accurate analysis and diagnosis. The book also encompasses computational vision processing techniques that handle complex data like physiological information, electronic healthcare records, and medical imaging data that assist in earlier prediction. Covering topics such as neural networks and disease detection, this reference work is ideal for industry professionals, practitioners, academicians, researchers, scholars, instructors, and students.

Cyber security is a key focus in the modern world as more private information is stored and saved online. In order to ensure vital information is protected from various cyber threats, it is essential to develop a thorough understanding of technologies that can address cyber security challenges. Artificial intelligence has been recognized as an important technology that can be employed successfully in the cyber security sector. Due to this, further study on the potential uses of artificial intelligence is required. The Handbook of Research on Cyber Security Intelligence and Analytics discusses critical artificial intelligence technologies that are utilized in cyber security and considers various cyber security issues and their optimal solutions supported by artificial intelligence. Covering a range of topics such as malware, smart grid, data breachers, and machine learning, this major reference work is ideal for security analysts, cyber security specialists, data analysts, security professionals, computer scientists, government officials, researchers, scholars, academicians, practitioners, instructors, and students.

Weather forecasting and climate behavioral analysis have traditionally been done using complicated physics models and accompanying atmospheric variables. However, the traditional approaches lack common tools, which can lead to incomplete information about the weather and climate conditions, in turn affecting the prediction accuracy rate. To address these problems, the advanced technological aspects through the spectrum of artificial intelligence of things (AIoT) models serve as a budding solution. Further study on artificial intelligence of things and how it can be utilized to improve weather forecasting and climatic behavioral analysis is crucial to appropriately employ the technology. Artificial Intelligence of Things for Weather Forecasting and Climatic Behavioral Analysis discusses practical applications of artificial intelligence of things for interpretation of weather patterns and how weather information can be used to make critical decisions about harvesting, aviation, etc. This book also considers artificial intelligence of things issues such as managing natural disasters that impact the lives of millions. Covering topics such as deep learning, remote sensing, and meteorological applications, this reference work is ideal for data scientists, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students.

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.

Professor Judea Pearl won the 2011 Turing Award "for fundamental contributions to artificial intelligence through the development of a calculus for probabilistic and causal reasoning." This book contains the original articles that led to the award, as well as other seminal works, divided into four parts: heuristic search, probabilistic reasoning, causality, first period (1988-2001), and causality, recent period (2002-2020). Each of these parts starts with an introduction written by Judea Pearl. The volume also contains original, contributed articles by leading researchers that analyze, extend, or assess the influence of Pearl's work in different fields: from AI, Machine Learning, and Statistics to Cognitive Science, Philosophy, and the Social Sciences. The first part of the volume includes a biography, a transcript of his Turing Award Lecture, two interviews, and a selected bibliography annotated by him.

As technology spreads globally, researchers and scientists continue to develop and study the strategy behind creating artificial life. This research field is ever expanding, and it is essential to stay current in the contemporary trends in artificial life, artificial intelligence, and machine learning. This an important topic for researchers and scientists in the field as well as industry leaders who may adapt this technology. The Handbook of Research on New Investigations in Artificial Life, AI, and Machine Learning provides concepts, theories, systems, technologies, and procedures that exhibit properties, phenomena, or abilities of any living system or human. This major reference work includes the most up-to-date research on techniques and technologies supporting AI and machine learning. Covering topics such as behavior classification, quality control, and smart medical devices, it serves as an essential resource for graduate students, academicians, stakeholders, practitioners, and researchers and scientists studying artificial life, cognition, AI, biological inspiration, machine learning, and more.

The application of artificial intelligence technology to 5G wireless communications is now appropriate to address the design of optimized physical layers, complicated decision-making, network management, and resource optimization tasks within networks. In exploring 5G wireless technologies and communication systems, artificial intelligence is a powerful tool and a research topic with numerous potential fields of application that require further study. Applications of Artificial Intelligence in Wireless Communication Systems explores the applications of artificial intelligence for the optimization of wireless communication systems, including channel models, channel state estimation, beamforming, codebook design, signal processing, and more. Covering key topics such as neural networks, deep learning, and wireless systems, this reference work is ideal for computer scientists, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students.

The artificial intelligence subset machine learning has become a popular technique in professional fields as many are finding new ways to apply this trending technology into their everyday practices. Two fields that have majorly benefited from this are pattern recognition and information security. The ability of these intelligent algorithms to learn complex patterns from data and attain new performance techniques has created a wide variety of uses and applications within the data security industry. There is a need for research on the specific uses machine learning methods have within these fields, along with future perspectives. Machine Learning Techniques for Pattern Recognition and Information Security is a collection of innovative research on the current impact of machine learning methods within data security as well as its various applications and newfound challenges. While highlighting topics including anomaly detection systems, biometrics, and intrusion management, this book is ideally designed for industrial experts, researchers, IT professionals, network developers, policymakers, computer scientists, educators, and students seeking current research on implementing machine learning tactics to enhance the performance of information security.