Regulating Hate Speech Created By Generative Ai
Download Regulating Hate Speech Created By Generative Ai PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Regulating Hate Speech Created By Generative Ai book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Regulating Hate Speech Created by Generative AI
Author: Jay Liebowitz
language: en
Publisher: Auerbach Publications
Release Date: 2024-08-02
Regulating Hate Speech Created by Generative AI explores the new hybrid space of Human Machine Interaction (HMI) in which hate speech is represented and computed through algorithms and AI generative systems. The book is exploratory because there are still many problem-solving challenges to be faced. It is also innovative because it is not assuming that solutions lie only in technological advancements but on a broader scale. In this sense, large language models can and are being considered from a holistic view (i.e., from the different dimensions and layers of regulatory and legal governance). Highlights of the book include: Generative AI and social engines of hate An introduction to generative Artificial Intelligence application, trends, and ethics The mechanics and validation of generative AI outcomes An evaluation of Generative AI for hate speech detection Best practices and key considerations for AI regulation Using GenAI capabilities for early detection of threats in the digital environment. This book is a hard look at ways to regulate generative AI to reduce online hate and secure justice in a digital environment. Featuring research and offering practical guidelines, the book examines guidelines for regulating generative AI models, so they do not contribute to online hate disinformation and imagery.
Regulating Hate Speech Created by Generative AI
Regulating Hate Speech Created by Generative AI explores the new hybrid space of Human Machine Interaction (HMI) in which hate speech is represented and computed through algorithms and AI generative systems. The book is exploratory because there are still many problem-solving challenges to be faced. It is also innovative because it is not assuming that solutions lie only in technological advancements but on a broader scale. In this sense, large language models can and are being considered from a holistic view (i.e., from the different dimensions and layers of regulatory and legal governance). Highlights of the book include: Generative AI and social engines of hate An introduction to generative Artificial Intelligence application, trends, and ethics The mechanics and validation of generative AI outcomes An evaluation of Generative AI for hate speech detection Best practices and key considerations for AI regulation Using GenAI capabilities for early detection of threats in the digital environment. This book is a hard look at ways to regulate generative AI to reduce online hate and secure justice in a digital environment. Featuring research and offering practical guidelines, the book examines guidelines for regulating generative AI models, so they do not contribute to online hate disinformation and imagery.
Building Trust in the Generative Artificial Intelligence Era
Author: Joanna Paliszkiewicz
language: en
Publisher: Taylor & Francis
Release Date: 2025-06-27
In an era where generative artificial intelligence (AI) is reshaping industries and daily life, trust has become a cornerstone for its successful adoption and application. Building Trust in the Generative Artificial Intelligence Era: Technology Challenges and Innovations explores how trust can be built, maintained, and evaluated in a world increasingly reliant on AI technologies. Designed to be accessible to a broad audience, thi book blends theoretical insights with practical approaches, offering readers a comprehensive understanding of the topic. This book is divided into three parts. The first part examines the foundations of trust in generative AI, highlighting trends and ethical challenges such as "greenwashing" and remote work dynamics. The second part provides actionable frameworks and tools for assessing and enhancing trust, focusing on topics like cybersecurity, transparency, and explainability. The final section presents global case studies exploring university students' perceptions of ChatGPT, generative AI's applications in European agriculture, and its transformative impact on financial systems. By addressing both the opportunities and risks of generative AI, this book delivers groundbreaking insights for academics, professionals, and policymakers worldwide. It emphasizes practical solutions, ensuring readers gain the knowledge needed to navigate the evolving technological landscape and foster trust in transformative AI systems.