This monograph introduces readers to core theories and applications in the chatbot AI context. Although AI is attracting significant attention, there is a literature gap and lack of practical guidelines on the key drivers of chatbot efficiency and agency capacity. There is a caveat between algorithmic explanations and actionable understanding, despite the acknowledged importance of inherently human-centric properties. Addressing these gaps, this state-of-the-art book offers a distinctive combination of content, theory, practice evaluation, and a holistic framework encompassing cognitive, emotional and social aspects, focusing on how to enhance AI agency and user experience. The framework aims to drive design, encouraging development of intelligent systems, techniques to evaluate chatbot with purposes, to appropriately meet user needs and market demand for responsible and explainable AI, XAI. Avenues for transforming business and life by implementing new generation AI systems are further discussed, as well as recommendations to overcome consumer resistance and advice for policy measures to reduce risks given the AI boost. While the community is still in an exploratory mode, we hope “The Rise of AI User Applications: Chatbots Integration Foundations and Trends” provides the needed understanding and will inspire researchers across disciplines to combine their efforts and work together on this very intriguing topic.

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

Librarians are uniquely positioned to rise to the challenge that artificial intelligence (AI) presents to the field. Libraries and their like have existed for millennia; they progress with society, altering and adapting their services to meet the information needs of their communities. The Rise of AI collects projects, collaborations, and future uses from academic librarians who have begun to embrace AI in their work. In three parts--User Services, Collections and Discovery, and Toward Future Applications--it explores: machine translation creating incubation spaces robotics combining information literacy initiatives with AI literacy fostering partnerships with other on-campus groups integrating AI technology into collections to enhance discoverability using AI to refine metadata for images, articles, and theses machine learning The Rise of AI introduces implications and applications of artificial intelligence in academic libraries and hopes to provoke conversations and inspire new ways of engaging with the technology. As the discussion surrounding ethics, bias, and privacy in AI continues to grow, librarians will be called to make informed decisions and position themselves as leaders in this discourse.

Artificial intelligence is emerging as a game-changer in the business world, with impacts across all sectors. AI allows business to process massive amounts of data instantaneously, and to scale solutions at almost zero marginal cost, forcing companies to adapt and reimagine their business and operations. The Rise of AI-Powered Companies examines some of the most successful examples of companies using artificial intelligence to their advantage. From AI-enabled countries across the globe that stayed resilient and strong in the face of COVID-19, to Business-to-Consumer businesses that transformed their product development processes thanks to unprecedented amounts of consumer data, increasing their revenues manifold along the way. The book then delves into the critical enablers to becoming AI-powered and the critical steps to activate and integrate them within business organizations. Starting with data strategy, it examines new forms of data sharing and how companies should think about governance and privacy risks. It then focuses on human–AI collaboration and its role in building a stronger team culture. Finally, "Responsible AI" is discussed as well as the impact of AI-powered businesses on society at large. AI-powered companies will become the norm in the years to come. By unpacking and showcasing the major steps of a successful AI transformation, this book will help guide organizations in making the critical leap to become AI-powered—essential to survive and remain competitive in the near future.

How will AI change our world within twenty years? A pioneering technologist and acclaimed writer team up for a “dazzling” (The New York Times) look at the future that “brims with intriguing insights” (Financial Times). This edition includes a new foreword by Kai-Fu Lee. A BEST BOOK OF THE YEAR: The Wall Street Journal, The Washington Post, Financial Times Long before the advent of ChatGPT, Kai-Fu Lee and Chen Qiufan understood the enormous potential of artificial intelligence to transform our daily lives. But even as the world wakes up to the power of AI, many of us still fail to grasp the big picture. Chatbots and large language models are only the beginning. In this “inspired collaboration” (The Wall Street Journal), Lee and Chen join forces to imagine our world in 2041 and how it will be shaped by AI. In ten gripping, globe-spanning short stories and accompanying commentary, their book introduces readers to an array of eye-opening settings and characters grappling with the new abundance and potential harms of AI technologies like deep learning, mixed reality, robotics, artificial general intelligence, and autonomous weapons.

Increasingly, business leaders and managers recognize that machine learning offers their companies immense opportunities for competitive advantage. But most discussions of machine learning are intensely technical or academic, and don't offer practical information leaders can use to identify, evaluate, plan, or manage projects. Deploying Machine Learning fills that gap, helping them clarify exactly how machine learning can help them, and collaborate with technologists to actually apply it successfully. You'll learn: What machine learning is, how it compares to "big data" and "artificial intelligence," and why it's suddenly so important What machine learning can do for you: solutions for computer vision, natural language processing, prediction, and more How to use machine learning to solve real business problems -- from reducing costs through improving decision-making and introducing new products Separating hype from reality: identifying pitfalls, limitations, and misconceptions upfront Knowing enough about the technology to work effectively with your technical team Getting the data right: sourcing, collection, governance, security, and culture Solving harder problems: exploring deep learning and other advanced techniques Understanding today's machine learning software and hardware ecosystem Evaluating potential projects, and addressing workforce concerns Staffing your project, acquiring the right tools, and building a workable project plan Interpreting results -- and building an organization that can increasingly learn from data Using machine learning responsibly and ethically Preparing for tomorrow's advances The authors conclude with five chapter-length case studies: image, text, and video analysis, chatbots, and prediction applications. For each, they don't just present results: they also illuminate the process the company undertook, and the pitfalls it overcame along the way.