Artificial Intelligence Tools for Teaching, Writing & Research

This book will provide a global perspective on AI and the challenges it represents, and will focus on the digital ethics surrounding AI technology.

This open access book provides a state-of-the-art overview of current machine learning research and its exploitation in various application areas. It has become apparent that the deep integration of artificial intelligence (AI) methods in products and services is essential for companies to stay competitive. The use of AI allows large volumes of data to be analyzed, patterns and trends to be identified, and well-founded decisions to be made on an informative basis. It also enables the optimization of workflows, the automation of processes and the development of new services, thus creating potential for new business models and significant competitive advantages. The book is divided in two main parts: First, in a theoretically oriented part, various AI/ML-related approaches like automated machine learning, sequence-based learning, deep learning, learning from experience and data, and process-aware learning are explained. In a second part, various applications are presented that benefit from the exploitation of recent research results. These include autonomous systems, indoor localization, medical applications, energy supply and networks, logistics networks, traffic control, image processing, and IoT applications. Overall, the book offers professionals and applied researchers an excellent overview of current exploitations, approaches, and challenges of AI/ML-related research.

This open access collection of AI ethics case studies is the first book to present real-life case studies combined with commentaries and strategies for overcoming ethical challenges. Case studies are one of the best ways to learn about ethical dilemmas and to achieve insights into various complexities and stakeholder perspectives. Given the omnipresence of AI ethics in academic, policy and media debates, the book will be suitable for a wide range of audiences, from scholars of different disciplines (e.g. AI science, ethics, politics, philosophy, economics) to policy-makers, lobbying NGOs, teachers and the educated public.

Today, many Americans are concerned about the impact that artificial intelligence and machine learning will have on jobs. This book examines the impact of these factors on the workforce, including issues related to worker displacement, retraining of the current workforce, and developing a skilled technical workforce of the future that can thrive in an economy in which AI increasingly plays a role.

The emergence of artificial intelligence has triggered enthusiasm and promise of boundless opportunities as much as uncertainty about its limits. The contributions to this volume explore the limits of AI, describe the necessary conditions for its functionality, reveal its attendant technical and social problems, and present some existing and potential solutions. At the same time, the contributors highlight the societal and attending economic hopes and fears, utopias and dystopias that are associated with the current and future development of artificial intelligence.

Current and Future Application of Artificial Intelligence in ClinicalMedicine presents updateson the application of machine learning and deep learning techniques in medicalprocedures. . Chapters in the volume have been written by outstandingcontributors from cancer and computer science institutes with the goal of providing updated knowledge to the reader. Topics covered in the bookinclude 1) Artificial Intelligence (AI) applications in cancer diagnosis and therapy,2) Updates in AI applications in the medical industry, 3) the use of AI in studyingthe COVID-19 pandemic in China, 4) AI applications in clinical oncology(including AI-based mining for pulmonary nodules and the use of AI inunderstanding specific carcinomas), 5) AI inmedical imaging. Each chapter presents information on related sub topics in areader friendly format. The combination of expert knowledge and multidisciplinary approaches highlightedin the book make it a valuable source of information for physicians andclinical researchers active in the field of cancer diagnosis and treatment(oncologists, oncologic surgeons, radiation oncologists, nuclear medicinephysicians, and radiologists) and computer science scholars seeking tounderstand medical applications of artificial intelligence.