Detecting Hate Speech in Human and AI-Generated Content : Techniques, Bias Mitigation, and Ethical Considerations

Mohammad Arsalan

ISBN 13: 9798337330631

Published by IGI GLOBAL SCIENTIFIC PUBLISHING, 2025

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - As digital communication becomes increasingly pervasive, the detection of hate speech in both human and AI-generated content has emerged as a critical concern for online safety. The use of harmful language across social media platforms and content generated by language models poses significant challenges in identifying toxic discourse. Traditional moderation methods often fall short in recognizing nuances prompting the integration of machine learning and natural language processing techniques to enhance detection accuracy. This evolving field underscores the need for robust systems capable of distinguishing between free expression and harmful language in this era. Detecting Hate Speech in Human and AI-Generated Content: Techniques, Bias Mitigation, and Ethical Considerations addresses the pressing challenge of hate speech detection across both AI-generated and human-generated content. It fills a crucial gap, providing a dual-focused approach to detect and manage hate speech effectively in this new, mixed-content landscape. Covering topics such as deepfakes, moderation, and social media, this book is an excellent resource for researchers, academicians, students, policymakers, and more.

Seller Inventory # 9798337330631

Bibliographic Details

• Title: Detecting Hate Speech in Human and AI-Generated Content : Techniques, Bias Mitigation, and Ethical Considerations
• Publisher: IGI GLOBAL SCIENTIFIC PUBLISHING
• Publication Date: 2025
• Language: English
• ISBN 13: 9798337330631
• Binding: Buch
• Condition: Neu
• Dimensions: 260W x 183H x 29D millimeters 260 millimeters width by 183 millimeters height by 29 millimeters depth
• Weight: 1061 grams

About this title

Synopsis

As digital communication becomes increasingly pervasive, the detection of hate speech in both human and AI-generated content has emerged as a critical concern for online safety. The use of harmful language across social media platforms and content generated by language models poses significant challenges in identifying toxic discourse. Traditional moderation methods often fall short in recognizing nuances prompting the integration of machine learning and natural language processing techniques to enhance detection accuracy. This evolving field underscores the need for robust systems capable of distinguishing between free expression and harmful language in this era. Detecting Hate Speech in Human and AI-Generated Content: Techniques, Bias Mitigation, and Ethical Considerations addresses the pressing challenge of hate speech detection across both AI-generated and human-generated content. It fills a crucial gap, providing a dual-focused approach to detect and manage hate speech effectively in this new, mixed-content landscape. Covering topics such as deepfakes, moderation, and social media, this book is an excellent resource for researchers, academicians, students, policymakers, and more.

About the Author

Mehul Mahrishi is currently working as an Associate Professor in the faculty of computer Science & Engineering at the Swami Keshvanand Institute of Technology, Management and Gramothan, Jaipur - India. He is a Professional Member of IEEE Delhi Section, Life Member of Institution of Engineers, India (L-IEI) and Life member of International Association of Engineers (IAENG). He was a member of an Indian contingent of BRICS International Forum that travelled to Moscow, Russia to attend Russian Energy Week-2018 and BRICS Youth Energy Summit. He has published more than 20 research papers in national and international Journals/conferences including 19th ISDA, 4th SoCTA, 3rd International Conference on Machine Learning and Computing (ICMLC 2011), 3rd IACC 2013 and chapters in books. He has also participated in a range of forums by Infosys, TCS, and WIPRO-Mission 10 X, IBM etc. His research activities are currently twofold: while the first research activity is set to explore the developmental enhancements in applications in computer vision; the second major research theme focused on the emerging capabilities of parallel and cloud computing. Mr. Mahrishi is rewarded at number of occasions in various domains including Recognition as an active reviewer by Journal of Parallel and Distributed Computing (JPDC, Elsevier, and SCI & Scopus Indexed), IEEE continuing education certification for "Cloud Computing Enable Technologies and Recognition for outstanding performance in Campus Connect Program by Infosys, India.