This book establishes the foundations needed to realize the ultimate goals for artificial intelligence, such as autonomy and trustworthiness. Aimed at scientists, researchers, technologists, practitioners, and students, it brings together contributions offering the basics, the challenges and the state-of-the-art on trusted autonomous systems in a single volume. The book is structured in three parts, with chapters written by eminent researchers and outstanding practitioners and users in the field. The first part covers foundational artificial intelligence technologies, while the second part covers philosophical, practical and technological perspectives on trust. Lastly, the third part presents advanced topics necessary to create future trusted autonomous systems. The book augments theory with real-world applications including cyber security, defence and space.

This book establishes the foundations needed to realize the ultimate goals for artificial intelligence, such as autonomy and trustworthiness.Aimed at scientists, researchers, technologists, practitioners, and students, it brings together contributions offering the basics, the challenges and the state-of-the-art on trusted autonomous systems in a single volume.The book is structured in three parts, with chapters written by eminent researchers and outstanding practitioners and users in the field. The first part covers foundational artificial intelligence technologies, while the second part covers philosophical, practical and technological perspectives on trust. Lastly, the third part presents advanced topics necessary to create future trusted autonomous systems.The book augments theory with real-world applications including cybersecurity, defence and space. This work was published by Saint Philip Street Press pursuant to a Creative Commons license permitting commercial use. All rights not granted by the work's license are retained by the author or authors.

Trust in Human-Robot Interaction addresses the gamut of factors that influence trust of robotic systems. The book presents the theory, fundamentals, techniques and diverse applications of the behavioral, cognitive and neural mechanisms of trust in human-robot interaction, covering topics like individual differences, transparency, communication, physical design, privacy and ethics. - Presents a repository of the open questions and challenges in trust in HRI - Includes contributions from many disciplines participating in HRI research, including psychology, neuroscience, sociology, engineering and computer science - Examines human information processing as a foundation for understanding HRI - Details the methods and techniques used to test and quantify trust in HRI

Personal motivation. The dream of creating artificial devices that reach or outperform human inteUigence is an old one. It is also one of the dreams of my youth, which have never left me. What makes this challenge so interesting? A solution would have enormous implications on our society, and there are reasons to believe that the AI problem can be solved in my expected lifetime. So, it's worth sticking to it for a lifetime, even if it takes 30 years or so to reap the benefits. The AI problem. The science of artificial intelligence (AI) may be defined as the construction of intelligent systems and their analysis. A natural definition of a system is anything that has an input and an output stream. Intelligence is more complicated. It can have many faces like creativity, solving prob lems, pattern recognition, classification, learning, induction, deduction, build ing analogies, optimization, surviving in an environment, language processing, and knowledge. A formal definition incorporating every aspect of intelligence, however, seems difficult. Most, if not all known facets of intelligence can be formulated as goal driven or, more precisely, as maximizing some utility func tion. It is, therefore, sufficient to study goal-driven AI; e. g. the (biological) goal of animals and humans is to survive and spread. The goal of AI systems should be to be useful to humans.

Argues against the conceptions of individual autonomy which are widely relied on in bioethics.

Dr. Greg Zacharias, former Chief Scientist of the United States Air Force (2015-18), explores next steps in autonomous systems (AS) development, fielding, and training. Rapid advances in AS development and artificial intelligence (AI) research will change how we think about machines, whether they are individual vehicle platforms or networked enterprises. The payoff will be considerable, affording the US military significant protection for aviators, greater effectiveness in employment, and unlimited opportunities for novel and disruptive concepts of operations. Autonomous Horizons: The Way Forward identifies issues and makes recommendations for the Air Force to take full advantage of this transformational technology.

Providing a high level of autonomy for a human-machine team requires assumptions that address behavior and mutual trust. The performance of a human-machine team is maximized when the partnership provides mutual benefits that satisfy design rationales, balance of control, and the nature of autonomy. The distinctively different characteristics and features of humans and machines are likely why they have the potential to work well together, overcoming each other's weaknesses through cooperation, synergy, and interdependence which forms a "collective intelligence. Trust is bidirectional and two-sided; humans need to trust AI technology, but future AI technology may also need to trust humans.Putting AI in the Critical Loop: Assured Trust and Autonomy in Human-Machine Teams focuses on human-machine trust and "assured performance and operation in order to realize the potential of autonomy. This book aims to take on the primary challenges of bidirectional trust and performance of autonomous systems, providing readers with a review of the latest literature, the science of autonomy, and a clear path towards the autonomy of human-machine teams and systems. Throughout this book, the intersecting themes of collective intelligence, bidirectional trust, and continual assurance form the challenging and extraordinarily interesting themes which will help lay the groundwork for the audience to not only bridge the knowledge gaps, but also to advance this science to develop better solutions. - Assesses the latest research advances, engineering challenges, and the theoretical gaps surrounding the question of autonomy - Reviews the challenges of autonomy (e.g., trust, ethics, legalities, etc.), including gaps in the knowledge of the science - Offers a path forward to solutions - Investigates the value of trust by humans of HMTs, as well as the bidirectionality of trust, understanding how machines learn to trust their human teammates

Can you teach a child to be kind? This vital question is taking on a new urgency as our culture grows ever more abrasive and divided. We all want our kids to be kind. But that is not the same as knowing what to do when you catch your son being unkind. A world-renowned developmental psychologist, Dr. Thomas Lickona has led the character education movement in schools for forty years. Now he shares with parents the vital tools they need to bring peace and foster cooperation at home. Kindness doesn’t stand on its own. It needs a supporting cast of other essential virtues—like courage, self-control, respect, and gratitude. With concrete examples drawn from the many families Dr. Lickona has worked with over the years and clear tips you can act on tonight, How to Raise Kind Kids will help you give and get respect, hold family meetings to tackle persistent problems, discipline in a way that builds character, and improve the dynamic of your relationship with your children while putting them on the path to a happier and more fulfilling life.

This book constitutes the refereed proceedings of the 17th International Symposium on Automated Technology for Verification and Analysis, ATVA 2019, held in Taipei, Taiwan in October 2019. The 24 regular papers presented together with 3 tool papers were carefully reviewed and selected from 65 submissions. The symposium is dedicated to the promotion of research on theoretical and practical aspects of automated analysis, verification and synthesis by providing a forum for interaction between the regional and the international research communities and industry in the field. The papers focus on cyber-physical systems; runtime techniques; testing; automata; synthesis; stochastic systems and model checking.

Personal autonomy is often lauded as a key value in contemporary Western bioethics, and the claim that there is an important relationship between autonomy and rationality is often treated as an uncontroversial claim in this sphere. Yet, there is also considerable disagreement about how we should cash out the relationship between rationality and autonomy. In particular, it is unclear whether a rationalist view of autonomy can be compatible with legal judgments that enshrine a patient's right to refuse medical treatment, regardless of whether ". . . the reasons for making the choice are rational, irrational, unknown or even non-existent". In this book, I bring recent philosophical work on the nature of rationality to bear on the question of how we should understand autonomy in contemporary bioethics. In doing so, I develop a new framework for thinking about the concept, one that is grounded in an understanding of the different roles that rational beliefs and rational desires have to play in personal autonomy. Furthermore, the account outlined here allows for a deeper understanding of different form of controlling influence, and the relationship between our freedom to act, and our capacity to decide autonomously. I contrast my rationalist with other prominent accounts of autonomy in bioethics, and outline the revisionary implications it has for various practical questions in bioethics in which autonomy is a salient concern, including questions about the nature of informed consent and decision-making capacity.