Today, the convergence of Artificial Intelligence (AI) and Big Data has revolutionized industries worldwide, driving business growth and reshaping societies. While these technologies have yielded remarkable benefits, many developing countries face challenges in harnessing their potential due to inadequate data collection and availability. Emerging Advancements in AI and Big Data Technologies in Business and Society delves into the profound impact of AI and Big Data on the digital landscape and their transformative influence on social, economic, and political spheres. With a historical overview of AI's evolution and its operational definition, this book explores interconnected subfields such as problem-solving, intelligent agents, natural language processing, computer vision, and machine learning. AI is hailed as the fourth industrial revolution and the widespread use of AI technologies prompts discussions about their applications, performances, and societal impact. This book serves as a comprehensive guide for academics, researchers, and students in universities and engineering schools. It also caters to policymakers, government officers, corporate leaders, technology directors, and managers seeking to understand the potential of AI and Big Data. Additionally, libraries and information centers catering to the needs of these professionals will find this book an essential resource.

Companies that don't use AI to their advantage will soon be left behind. Artificial intelligence and machine learning will drive a massive reshaping of the economy and society. What should you and your company be doing right now to ensure that your business is poised for success? These articles by AI experts and consultants will help you understand today's essential thinking on what AI is capable of now, how to adopt it in your organization, and how the technology is likely to evolve in the near future. Artificial Intelligence: The Insights You Need from Harvard Business Review will help you spearhead important conversations, get going on the right AI initiatives for your company, and capitalize on the opportunity of the machine intelligence revolution. Catch up on current topics and deepen your understanding of them with the Insights You Need series from Harvard Business Review. Featuring some of HBR's best and most recent thinking, Insights You Need titles are both a primer on today's most pressing issues and an extension of the conversation, with interesting research, interviews, case studies, and practical ideas to help you explore how a particular issue will impact your company and what it will mean for you and your business.

Blockchain has become the cornerstone of technologies, supported by others including Big Data and Artificial Intelligence (AI). Originating from cryptocurrency, it transcends boundaries, finding resonance in finance, healthcare, e-governance, and beyond. While blockchain relies on a peer-to-peer approach, enabling nodes to collaborate without the shackles of a central authority, appropriate monitoring and updating of these technologies is a constant necessity. This is especially true for healthcare data systems, where data privacy and security concerns, especially with sensitive health information are paramount. Threads of automation in artificial intelligence (AI) weave through sectors such as business, finance, healthcare, marketing, and governance. Industrial Applications of Big Data, AI, and Blockchain delves into the pulsating realms of big data, AI, and blockchain. From natural language processing's eloquent interpretation of human language to the prowess of AI algorithms in predictive tasks, this book explores how AI enhances decision-making accuracy, catalyzing a paradigm shift in diverse industries. This book is ideal for researchers, business visionaries, tech enthusiasts, and curious minds eager to fathom the transformative potential of these technologies.

As smart cities become more prevalent, the need for explainable AI (XAI) applications has become increasingly important. Advances in Explainable AI Applications for Smart Cities is a co-edited book that showcases the latest research and development in XAI for smart city applications. This book covers a wide range of topics, including medical diagnosis, finance and banking, judicial systems, military training, manufacturing industries, autonomous vehicles, insurance claim management, and cybersecurity solutions. Through its diverse case studies and research, this book provides valuable insights into the importance of XAI in smart city applications. This book is an essential resource for undergraduate and postgraduate students, researchers, academicians, industry professionals, and scientists working in research laboratories. It provides a comprehensive overview of XAI concepts, advantages over AI, and its applications in smart city development. By showcasing the impact of XAI on various smart city applications, the book enables readers to understand the importance of XAI in creating more sustainable and efficient smart cities. Additionally, the book addresses the open challenges and research issues related to XAI in modern smart cities, providing a roadmap for future research in this field. Overall, this book is a valuable resource for anyone interested in understanding the importance of XAI in smart city applications.

The rapid advancement of IoT and smart technologies poses significant challenges for academic scholars, including meeting new requirements such as reliability, quality of service, and energy efficiency. AIoT and Smart Sensing Technologies for Smart Devices, edited by Fadi ALTURJMAN, offers an invaluable solution by serving as a knowledge hub that brings together diverse research and professional contributions. This comprehensive book enables scholars to delve into topics like IoT-oriented applications, sustainable development, machine learning, and wireless networks, providing the necessary insights to navigate the complexities of IoT and smart technologies. Targeted at experts, researchers, and students, this book equips readers with the understanding needed to tackle the challenges in this dynamic field. Covering areas such as IoT paradigms, network security, machine learning approaches, and wireless network protocols, it serves as a guide for unlocking the potential of AIoT. With this resource, scholars can stay informed, explore innovative approaches, and actively contribute to the advancement of AIoT and smart technologies, making it a compelling solution for those grappling with the complexities of this transformative field.

In an era marked by rapid technological progress, women's safety remains a pressing concern despite strides toward gender equality. Women continue to grapple with safety challenges in both public and private spaces, enduring harassment, violence, and discrimination driven by entrenched societal norms and modern complexities. Amidst these challenges, harnessing the potential of artificial intelligence (AI) emerges as a promising avenue to reshape the landscape of women's safety. The groundbreaking book, AI Tools and Applications for Women’s Safety, curated by experts Sivaram Ponnusamy, Vibha Bora, Prema Daigavane, and Sampada Wazalwar, delves into the transformative power of AI to address the daily safety concerns women face. This timely volume explores innovative AI-driven resources and applications that redefine personal security, offering tailored protection through real-time threat assessment and emergency response coordination. With comprehensive insights spanning academia, law enforcement, policymaking, and advocacy, this book covers predictive safety analytics, smart surveillance, ethical considerations, and more. AI Tools and Applications for Women’s Safety not only sheds light on the promise of AI but also paves the way for informed discourse and meaningful action, ushering in a future defined by women's empowerment and security.

The rapid adoption of deep learning models has resulted in many business services becoming model services, yet most AI systems lack the necessary automation and industrialization capabilities. This leads to heavy reliance on manual operation and maintenance, which not only consumes power but also causes resource wastage and stability issues during system mutations. The inadequate self-adaptation of AI systems poses significant challenges in terms of cost-effectiveness and operational stability. Principles and Applications of Adaptive Artificial Intelligence, edited by Zhihan Lv from Uppsala University, Sweden, offers a comprehensive solution to the self-adaptation problem in AI systems. It explores the latest concepts, technologies, and applications of Adaptive AI, equipping academic scholars and professionals with the necessary knowledge to overcome the challenges faced by traditional business logic transformed into model services. With its problem-solving approach, real-world case studies, and thorough analysis, the Handbook provides practitioners with practical ideas and solutions, while also serving as a valuable teaching material and reference guide for students and educators in AI-related disciplines. By emphasizing self-adaptation, continuous model iteration, and dynamic learning based on real-time feedback, the book empowers readers to significantly enhance the cost-effectiveness and operational stability of AI systems, making it an indispensable resource for researchers, professionals, and students seeking to revolutionize their research and applications in the field of Adaptive AI.