This book examines how Gen AI is transforming how we learn, teach, and conduct research, offering an accessible and authoritative guide for scholars, educators, and professionals navigating the opportunities and risks of AI in the social sciences and humanities. Its unique for its SSH perspective, empirical depth, and strong ethical framing.
The book focuses on concepts to give readers a wider perspective on generative AI systems such as ChatGPT. It examines algorithmic elements pertaining to the improvement of current tools. It also examines how generative AI can lead to social benefits.
This book provides an up-to-date and easy-to-read introduction to Generative AI and its revolutionary contribution to building Industry 5.0. Written for both practitioners and interested readers, it is a clear and compelling overview of the technologies at the heart of the next industrial revolution.
Like its prequel, this book examines the 'nature/nurture' debate in language, while also asking how language came to be part of our human nature in the course of evolution. Considering the multidisciplinary context of these debates, this book is essential reading for academics and students in a range of fields.
This book examines language and communication in digital health, proposing a discourse-oriented approach to genetic literacy, applying it to the study of public engagement with direct-to-consumer (DTC) genetic testing. It will appeal to researchers and students in the areas of sociolinguistics, discourse analysis, and health communication.
This timely monograph explores the critical, yet often overlooked, role of genre in non-traditional authorship attribution studies, drawing from linguistics, rhetoric, stylistics, forensic linguistics, and computational methods—including Large Language Models (LLMs).