Generative AI Ethics: Meaning, Authorship, and Governance

Generative AI Ethics: Meaning, Authorship, and Governance examines the ethical challenges emerging from the rapid development and widespread adoption of generative artificial intelligence systems. Generative AI technologies—including large language models, image generators, and multimodal creative systems—are transforming how knowledge, culture, and creativity are produced. These systems raise new ethical questions about authorship, originality, responsibility, bias, and the governance of machine-generated content. Unlike earlier forms of artificial intelligence that focused primarily on prediction and automation, generative AI operates directly within domains of language, art, and communication, blurring the boundaries between human and machine creativity. This book provides a comprehensive exploration of these issues through four interconnected parts. The first establishes the philosophical and conceptual foundations of AI ethics, situating generative AI within broader traditions such as consequentialism, deontology, virtue ethics, and care ethics. The second examines questions of responsibility and governance, including accountability across the generative AI pipeline, transparency and disclosure, and emerging regulatory debates surrounding copyright, data governance, and model ownership. The third explores the societal implications of generative AI, addressing issues of inequality, representation, bias, and the psychological and cultural effects of synthetic media. The final section considers future directions for ethical practice in education, research, and creative industries, as well as broader philosophical debates about posthuman and ecological perspectives on technology. Across these discussions, the book argues that generative AI ethics must extend beyond narrow technical concerns to address deeper questions about creativity, knowledge production, and social responsibility. Ethical governance of generative AI requires not only regulatory frameworks but also institutional practices, cultural awareness, and new forms of human–AI collaboration grounded in transparency, accountability, and care. This work forms part of the wider CloudPedagogy ecosystem exploring AI capability, governance, and responsible professional practice.Source repository:https://github.com/cloudpedagogy/cloudpedagogy-books