A Compendium Of Responsible Artificial Intelligence
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A Compendium of Responsible Artificial Intelligence
Taking a broad, multidisciplinary approach to the ethical, legal, and practical dimensions of developing AI, the book puts key issues such as bias, transparency, accountability, and privacy at center stage. From computer science through law and ethics into policy, it lays down the roadmap on which developers, data scientists, and policymakers could bring AI technologies properly attuned to societal values. This book can be read as a resource for those who want to be able to guide the development and deployment of responsibly controlled AI systems.
A Compendium of Responsible Artificial Intelligence
"The book 'A Compendium of Responsible Artificial Intelligence' is a comprehensive exploration of the ethical, legal, and practical aspects of AI development and deployment. It delves into the emerging field of responsible AI, which focuses on ensuring that AI technologies are designed and used in ways that are ethical, unbiased, and aligned with societal values. The book's aim is to provide a deep understanding of how AI systems should be developed and governed responsibly, addressing the increasing concerns surrounding AI, such as bias, transparency, accountability, and privacy. The project takes a multidisciplinary approach, drawing from computer science, ethics, law, and policy. It offers a practical roadmap for developers, data scientists, policymakers, and stakeholders to navigate the complex landscape of responsible AI. This book will serve as a resource for both beginners and experts in the field, helping them develop and implement AI solutions that adhere to ethical principles and legal standards. The primary aim of the book is to shed light on the critical issues surrounding AI and ethics, with a strong emphasis on promoting responsible AI development and usage. It's scope is extensive, covering a broad range of topics essential to understanding and implementing responsible AI"-- Provided by publisher.
Compendium of Neurosymbolic Artificial Intelligence
If only it were possible to develop automated and trainable neural systems that could justify their behavior in a way that could be interpreted by humans like a symbolic system. The field of Neurosymbolic AI aims to combine two disparate approaches to AI; symbolic reasoning and neural or connectionist approaches such as Deep Learning. The quest to unite these two types of AI has led to the development of many innovative techniques which extend the boundaries of both disciplines. This book, Compendium of Neurosymbolic Artificial Intelligence, presents 30 invited papers which explore various approaches to defining and developing a successful system to combine these two methods. Each strategy has clear advantages and disadvantages, with the aim of most being to find some useful middle ground between the rigid transparency of symbolic systems and the more flexible yet highly opaque neural applications. The papers are organized by theme, with the first four being overviews or surveys of the field. These are followed by papers covering neurosymbolic reasoning; neurosymbolic architectures; various aspects of Deep Learning; and finally two chapters on natural language processing. All papers were reviewed internally before publication. The book is intended to follow and extend the work of the previous book, Neuro-symbolic artificial intelligence: The state of the art (IOS Press; 2021) which laid out the breadth of the field at that time. Neurosymbolic AI is a young field which is still being actively defined and explored, and this book will be of interest to those working in AI research and development.