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This book studies the role of Artificial Intelligence (AI) in journalism. It traces the origin, growth and development of the media and communication industry in the globalized world and discusses the implications of technologies such as Augmented Reality, Virtual Reality and Extended Reality which have helped foster a communication revolution across the globe. The volume discusses technology-centric media theories in the context of AI and examines if AI has been a boon or bane for data journalism. It also looks at artificial intelligence in beat reporting, and citizen journalism, and analyses the social-cultural implications of artificial intelligence driven journalism and the ethical concerns arising from it. An important contribution, this book will be indispensable for students and researchers of media studies, communication studies, journalism, social media, technology studies, and digital humanities. It will also be useful for media professionals.
This book studies the role of Artificial Intelligence (AI) in journalism. It traces the origin, growth and development of the media and communication industry in the globalized world and discusses the implications of technologies such as Augmented Reality, Virtual Reality and Extended Reality which have helped foster a communication revolution across the globe. The volume discusses technology-centric media theories in the context of AI and examines if AI has been a boon or bane for data journalism. It also looks at artificial intelligence in beat reporting, and citizen journalism, and analyses the social-cultural implications of artificial intelligence driven journalism and the ethical concerns arising from it. An important contribution, this book will be indispensable for students and researchers of media studies, communication studies, journalism, social media, technology studies, and digital humanities. It will also be useful for media professionals.
This book discusses one of the major applications of artificial intelligence: the use of machine learning to extract useful information from multimodal data. It discusses the optimization methods that help minimize the error in developing patterns and classifications, which further helps improve prediction and decision-making. The book also presents formulations of real-world machine learning problems, and discusses AI solution methodologies as standalone or hybrid approaches. Lastly, it proposes novel metaheuristic methods to solve complex machine learning problems. Featuring valuable insights, the book helps readers explore new avenues leading toward multidisciplinary research discussions.
In today's rapidly evolving digital landscape, the power of Artificial Intelligence (AI) is increasingly recognized as organizations seek to disrupt and transform processes in order to drive innovation in their business models. However, despite substantial investments in AI implementation, recent research indicates that organizations are struggling to realize the expected benefits. Furthermore, many firms face challenges when it comes to effectively integrating AI applications into their existing organizational systems. To bridge this gap, there is an urgent need to deepen understanding of AI techniques, particularly in the context of Asian organizations, where diverse workforces, cultural differences, language barriers, and skill shortages present unique complexities. Exploring the Intersection of AI and Human Resources Management explores the methodologies, theories, and perspectives related to the application of AI in organizations. Focused on the convergence of Human Resource Management (HRM) and AI, this book aims to provide invaluable insights to academics, researchers, policymakers, organizational managers, advanced-level students, leaders, academicians, and government officials. By shedding light on the tools and applications of AI in optimizing human resources, this book expands the horizons of research and encourages the seamless integration of HRM and AI.
This edited book explores the many interesting questions that lie at the intersection between AI and HCI. It covers a comprehensive set of perspectives, methods and projects that present the challenges and opportunities that modern AI methods bring to HCI researchers and practitioners. The chapters take a clear departure from traditional HCI methods and leverage data-driven and deep learning methods to tackle HCI problems that were previously challenging or impossible to address. It starts with addressing classic HCI topics, including human behaviour modeling and input, and then dedicates a section to data and tools, two technical pillars of modern AI methods. These chapters exemplify how state-of-the-art deep learning methods infuse new directions and allow researchers to tackle long standing and newly emerging HCI problems alike. Artificial Intelligence for Human Computer Interaction: A Modern Approach concludes with a section on Specific Domains which covers a set of emerging HCI areas where modern AI methods start to show real impact, such as personalized medical, design, and UI automation.
Rapid advancements in mobile computing and communication technology and recent technological progress have opened up a plethora of opportunities. These advancements have expanded knowledge, facilitated global business, enhanced collaboration, and connected people through various digital media platforms. While these virtual platforms have provided new avenues for communication and self-expression, they also pose significant threats to our privacy. As a result, we must remain vigilant against the propagation of electronic violence through social networks. Cyberbullying has emerged as a particularly concerning form of online harassment and bullying, with instances of racism, terrorism, and various types of trolling becoming increasingly prevalent worldwide. Addressing the issue of cyberbullying to find effective solutions is a challenge for the web mining community, particularly within the realm of social media. In this context, artificial intelligence (AI) can serve as a valuable tool in combating the diverse manifestations of cyberbullying on the Internet and social networks. This book presents the latest cutting-edge research, theoretical methods, and novel applications in AI techniques to combat cyberbullying. Discussing new models, practical solutions, and technological advances related to detecting and analyzing cyberbullying is based on AI models and other related techniques. Furthermore, the book helps readers understand AI techniques to combat cyberbullying systematically and forthrightly, as well as future insights and the societal and technical aspects of natural language processing (NLP)-based cyberbullying research efforts. Key Features: Proposes new models, practical solutions and technological advances related to machine intelligence techniques for detecting cyberbullying across multiple social media platforms. Combines both theory and practice so that readers (beginners or experts) of this book can find both a description of the concepts and context related to the machine intelligence. Includes many case studies and applications of machine intelligence for combating cyberbullying.
This 5-volume HCII-DUXU 2023 book set constitutes the refereed proceedings of the 12th International Conference on Design, User Experience, and Usability, DUXU 2023, held as part of the 24th International Conference, HCI International 2023, which took place in Copenhagen, Denmark, in July 2023. A total of 1578 papers and 396 posters have been accepted for publication in the HCII 2023 proceedings from a total of 7472 submissions. The papers included in this volume set were organized in topical sections as follows: Part I: Design methods, tools and practices; emotional and persuasive design; Part II: Design case studies; and creativity and design education; Part III: Evaluation methods and techniques; and usability, user experience and technology acceptance studies; Part IV: Designing learning experiences; and chatbots, conversational agents and robots: design and user experience; Part V: DUXU for cultural heritage; and DUXU for health and wellbeing.
In today's rapidly evolving landscape, AI has become an indispensable tool for organizations seeking to enhance their understanding of customers, boost productivity, and foster stronger connections with their target audience. The Use of Artificial Intelligence in Digital Marketing: Competitive Strategies and Tactics is a comprehensive and timely exploration of the integration of artificial intelligence (AI) into the field of digital marketing. Authored by experts in the field, this book delves into the profound and far-reaching changes that AI is bringing to the digital marketing arena. It provides a detailed examination of how organizations can leverage AI technologies to gain a competitive edge in the market. By mastering these new technologies, companies can effectively navigate the dynamic digital landscape, optimize their marketing strategies, and deliver highly personalized content to their customers. Ideal for a wide range of audiences, including researchers, teachers, students, and executives, this book serves as a vital resource for those seeking to stay ahead of the curve in the ever-evolving world of digital marketing. Through its comprehensive coverage of AI applications in the field, it equips readers with the knowledge and insights necessary to make informed decisions, develop effective marketing strategies, and drive business growth.
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