As AI technologies evolve at an exponential pace there are many questions and challenges for IP and the IP system. The purpose of this IP policy toolkit is to provide policymakers with a framework to understand the state of play of AI innovation right now and to think about the future as AI becomes increasingly autonomous.

The first report in a new flagship series, WIPO Technology Trends, aims to shed light on the trends in innovation in artificial intelligence since the field first developed in the 1950s.

This open access book proposes a novel approach to Artificial Intelligence (AI) ethics. AI offers many advantages: better and faster medical diagnoses, improved business processes and efficiency, and the automation of boring work. But undesirable and ethically problematic consequences are possible too: biases and discrimination, breaches of privacy and security, and societal distortions such as unemployment, economic exploitation and weakened democratic processes. There is even a prospect, ultimately, of super-intelligent machines replacing humans. The key question, then, is: how can we benefit from AI while addressing its ethical problems? This book presents an innovative answer to the question by presenting a different perspective on AI and its ethical consequences. Instead of looking at individual AI techniques, applications or ethical issues, we can understand AI as a system of ecosystems, consisting of numerous interdependent technologies, applications and stakeholders. Developing this idea, the book explores how AI ecosystems can be shaped to foster human flourishing. Drawing on rich empirical insights and detailed conceptual analysis, it suggests practical measures to ensure that AI is used to make the world a better place.

"AI FOR GOOD-INDIA AND BEYOND" is a seminal work offering a comprehensive navigation into the evolution and current state of AI regulation in India, marking significant judicial decisions and emerging policies with a keen eye on their alignment with international laws/standards. The book advocates for a Human Rights-Centric Policy Approach promoting fairness, accountability, and transparency in the development of ethical AI systems. Analysing global trends and legal approaches towards AI governance, the authors provide a comparative panorama spanning the latest EU AI Act (2024) to enactments in Brazil, China, Japan, and the USA. Key features • Comprehensive Analysis: Detailed analysis of AI & laws, and policies in India and their global interplay. • Legal Frameworks: Exploration of the statutes and case laws that govern AI, highlighting the evolving legal landscape with real-life examples. • Ethical Considerations: Discussion on the ethical frameworks that must be considered for responsible AI management, including safety, inclusivity, equality, privacy, transparency, accountability, and protection of human values. • Policy Recommendations: Tailored recommendations for India, considering its unique position in the global market and potential for AI leadership. • International Perspectives: Examination of international frameworks and guidelines from major entities like the EU, OECD, and the UNESCO, offering a global context for comparison. • IPR and AI Interplay: A dedicated section on the relationship between AI and intellectual property rights, addressing concerns around AI-generated content, and ownership. • Civil and Criminal Liabilities: Insights into the complex issues of AI and legal liability, highlighting discussions of potential civil and criminal implications. • Legal Personhood of AI: An in-depth look at the concept of granting legal personhood to AI entities and the related legal and ethical implications. • Data Governance: The draft National Data Governance Framework Policy and its importance for managing government data and fostering an ecosystem for AI are covered. • Deeper Insights : 500 plus references for deeper understanding of the topics illustrated in the book

A key reading for leaders that outlines how to effectively innovate for the future and boost growth, while running the core business. - Alex Osterwalder, Co-author of Business Model Generation. Winner of the 2018 CMI Management Book of the Year Award for Innovation and Entrepeneurship The Corporate Startup is a practical guide for established companies that aspire to develop and sustain their innovation capabilities. * The world around us is changing rapidly. There is now more pressure on established companies to innovate. * The challenge most companies face is how to develop new products for new markets, while managing their core business at the same time. * The principles and practices outlined in this book provide companies with a blueprint of how to manage innovation while they execute on their core business. * The Corporate Startup provides frameworks, visualizations, templates, tools and methods that can be easily applied to develop new products and business models. This book helps organisations of all sizes to manage innovation. This playbook uses illustrated step-by- step guides to lead the reader through the processes to create an ecosystem that nurtures innovation at every level in a business. - Jury CMI Management Book of the Year. Big companies need to innovate or die. The question is how. Companies need a playbook; a process by which they can start the process of transforming their organizations into innovation engines. The Corporate Startup is that playbook. It provides a proven methodology --applying Lean Startup principles and more-- for building a culture of innovation. - Ben Yoskovitz, Co-Author of Lean Analytics and Founding Partner at Highline BETA.

“Essential Concepts and Techniques of AI & ML” is a comprehensive textbook designed to demystify the complexities of Artificial Intelligence and Machine Learning for learners at all levels. The book covers a broad spectrum of topics, starting with an overview of the history and evolution of AI and ML, and progressing to advanced techniques and applications. Readers will explore key concepts such as supervised and unsupervised learning, neural networks, data preprocessing, and model evaluation. Each chapter is carefully structured to provide a balance between theory and practice, with numerous examples, illustrations, and hands-on exercises. The book also delves into the ethical considerations surrounding AI and ML, ensuring that readers are aware of the broader implications of these technologies. Additionally, it introduces popular tools and frameworks, offering practical guidance on how to implement AI and ML models. Whether you are pursuing a career in AI and ML or simply want to understand the technologies driving today’s innovations, this textbook offers the essential knowledge and skills needed to navigate and contribute to this dynamic field.

Artificial Intelligence for Business: A Roadmap for Getting Started with AI will provide the reader with an easy to understand roadmap for how to take an organization through the adoption of AI technology. It will first help with the identification of which business problems and opportunities are right for AI and how to prioritize them to maximize the likelihood of success. Specific methodologies are introduced to help with finding critical training data within an organization and how to fill data gaps if they exist. With data in hand, a scoped prototype can be built to limit risk and provide tangible value to the organization as a whole to justify further investment. Finally, a production level AI system can be developed with best practices to ensure quality with not only the application code, but also the AI models. Finally, with this particular AI adoption journey at an end, the authors will show that there is additional value to be gained by iterating on this AI adoption lifecycle and improving other parts of the organization.

Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data

Fransman explains how innovation happens and which factors can help or hinder, by treating innovation as a systemic phenomenon, or ecosystem of players and processes. It will appeal to economists, other social scientists, business people, policy makers, and anyone interested in innovation and entrepreneurship.

"a provocative new book" — The New York Times AI-centric organizations exhibit a new operating architecture, redefining how they create, capture, share, and deliver value. Now with a new preface that explores how the coronavirus crisis compelled organizations such as Massachusetts General Hospital, Verizon, and IKEA to transform themselves with remarkable speed, Marco Iansiti and Karim R. Lakhani show how reinventing the firm around data, analytics, and AI removes traditional constraints on scale, scope, and learning that have restricted business growth for hundreds of years. From Airbnb to Ant Financial, Microsoft to Amazon, research shows how AI-driven processes are vastly more scalable than traditional processes, allow massive scope increase, enabling companies to straddle industry boundaries, and create powerful opportunities for learning—to drive ever more accurate, complex, and sophisticated predictions. When traditional operating constraints are removed, strategy becomes a whole new game, one whose rules and likely outcomes this book will make clear. Iansiti and Lakhani: Present a framework for rethinking business and operating models Explain how "collisions" between AI-driven/digital and traditional/analog firms are reshaping competition, altering the structure of our economy, and forcing traditional companies to rearchitect their operating models Explain the opportunities and risks created by digital firms Describe the new challenges and responsibilities for the leaders of both digital and traditional firms Packed with examples—including many from the most powerful and innovative global, AI-driven competitors—and based on research in hundreds of firms across many sectors, this is your essential guide for rethinking how your firm competes and operates in the era of AI.