This edited volume provides a broad and comprehensive picture of the intersection between Artificial Intelligence technology and Intellectual Property law, covering business and the basics of AI, the interactions between AI and patent law, copyright law, and IP administration, and the legal aspects of software and data.

Artificial Intelligence (AI) has become omnipresent in today's business environment: from chatbots to healthcare services to various ways of creating useful information. While AI has been increasingly used to optimize various creative and innovative processes, the integration of AI into products, services, and other operational procedures raises significant concerns across virtually all areas of intellectual property (IP) law. While AI has drawn extensive attention from IP experts globally, this is the first book providing a broad and comprehensive picture from the perspectives of the very nature of AI technology, its commercial implications, its interaction with different kinds of IP, IP administration, software and data, its social and economic impact on the innovation policy, and ultimately AI's eligibility as a legal entity.

The emergence of Artificial Intelligence (AI) has profound implications for intellectual property (IP) frameworks. While much of the discussion so far has focused on the legal implications, we focus on the economic dimension. We dissect AI's role as both a facilitator and disruptor of innovation and creativity. Recalling economic principles and reviewing relevant literature, we explore the evolving landscape of AI innovation incentives and the challenges it poses to existing IP frameworks. From patentability dilemmas to copyright conundrums, we find that there is a delicate balance between fostering innovation and safeguarding societal interests amidst rapid technological progress. We also point to areas where future economic research could offer valuable insights to policymakers.

This incisive Handbook offers novel theoretical and doctrinal insights alongside practical guidance on some of the most challenging issues in the field of artificial intelligence and intellectual property. Featuring all original contributions from a diverse group of international thought leaders, including top academics, judges, regulators and eminent practitioners, it offers timely perspectives and research on the relationship of AI to copyright, trademark, design, patent and trade secret law.

AI technologies have the potential to revolutionize various industries, including healthcare, finance, transportation, and entertainment. They can automate repetitive tasks, enhance decision-making processes, improve efficiency, and enable the development of innovative products and services. However, the rapid advancement of AI also raises significant challenges and implications for intellectual property rights". "AI systems generate valuable outputs, such as creative works, inventions, and data-driven insights. These outputs can be subject to intellectual property protection, which grants exclusive rights to the creators or owners of the intellectual assets. Intellectual property rights encompass various legal mechanisms, including copyright, patents, trademarks, and trade secrets, which are designed to incentivize innovation and creativity"-"As artificial intelligence continues to advance, the challenge lies in striking a balance between fostering innovation and protecting intellectual property. The future will require a nuanced approach that encourages creativity while addressing the ethical and legal implications of AI-driven inventions" "In the era of artificial intelligence, intellectual property rights will be at the forefront of the innovation landscape. The evolving nature of AI raises crucial questions about ownership, accountability, and the need for adaptive legal frameworks to safeguard the rights of creators and innovators in this rapidly changing landscape"

Artificial Intelligence (AI) is the most rapidly developing technology in the current Digital Age, but it is also the least defined, understood and adequately explained technological advance. This book brings together a group of leading experts who assess different aspects of AI from different disciplinary perspectives. The book argues that robots are not living systems but the creations of humans who must ultimately be accountable for the actions of the robots that they have invented. Robots do not have ownership entitlement. The book uses Intellectual Property Rights cases, evidence from roboticists, cybersecurity experts, Patent Court judges, technology officers, climate change scientists, economists, physicists and those from the legal profession to demonstrate that while AI can have very beneficial uses for many aspects of human economy and society, robots are not living systems autonomous from human decision making. This book will be useful to those in banking and insurance, cybersecurity, lawyers, judges, technology officers, economists, scientist inventors, computer scientists, large and small companies and postgraduate students.

Integral to the commercial law field, Intellectual Property (IP) knowledge is central to culture, innovation, and enterprise. Looking forward to the new academic norm, Teaching Intellectual Property Law: Strategy and Management uses experience as well as innovative, interactive, practice-based methods for teaching IP to examine the various ways through which to move on from ‘chalk and talk’ methods.

The Handbook of Research on AI and ML for Intelligent Machines and Systems offers a comprehensive exploration of the pivotal role played by artificial intelligence (AI) and machine learning (ML) technologies in the development of intelligent machines. As the demand for intelligent machines continues to rise across various sectors, understanding the integration of these advanced technologies becomes paramount. While AI and ML have individually showcased their capabilities in developing robust intelligent machine systems and services, their fusion holds the key to propelling intelligent machines to a new realm of transformation. By compiling recent advancements in intelligent machines that rely on machine learning and deep learning technologies, this book serves as a vital resource for researchers, graduate students, PhD scholars, faculty members, scientists, and software developers. It offers valuable insights into the key concepts of AI and ML, covering essential security aspects, current trends, and often overlooked perspectives that are crucial for achieving comprehensive understanding. It not only explores the theoretical foundations of AI and ML but also provides guidance on applying these techniques to solve real-world problems. Unlike traditional texts, it offers flexibility through its distinctive module-based structure, allowing readers to follow their own learning paths.