Namrata N. Wasatkar - Böcker

With the ever-increasing use of AI technologies, ethical considerations take on greater importance. Human-centric AI emphasizes transparency, making sure that AI systems work in a way that users can comprehend and trust. Additionally, it addresses bias and discrimination issues, ensuring fairness and inclusion in the design and implementation of AI apps. By emphasizing user experience, security, and human-centric AI, the goal is to improve collaboration between people and machines, rather than replacing human decisions, creating a future where technology is a force for good, benefiting both businesses and society. Written from a technological point of view, Industry 5.0 for Society 5.0 explores the impact of cutting-edge technologies, including the Internet of Things, cloud, artificial intelligence, and digital twin, on individuals and community, and considers how they can be used to solve societal problems. The book considers how these technologies can positively affect industry, healthcare, agriculture, design and manufacture, contributing to the development of a sustainable environment that ultimately creates a positive and mutually beneficial relationship between people and AI.Presents the fundamentals, challenges and advancements in AI required for Industry 5.0 to be beneficial to societyFocuses on human-centric AI and how it can be used to create more sustainable industryExplores the ethical considerations and regulatory aspects of Edge AI, helping readers navigate the responsible use of this technology

This book discusses the best research roadmaps, strategies, and challenges in data-centric approach of artificial intelligence (AI) in various domains. It presents comparative studies of model-centric and data-centric AI. It also highlights different phases in data-centric approach and data-centric principles. The book presents prominent use cases of data-centric AI. It serves as a reference guide for researchers and practitioners in academia and industry.

This book discusses the best research roadmaps, strategies, and challenges in data-centric approach of artificial intelligence (AI) in various domains. It also highlights different phases in data-centric approach and data-centric principles. The book presents prominent use cases of data-centric AI.