The Ethical Paradox of AI-Generated Texts: Investigating the Moral Responsibility in Generative Models

Abstract

The rapid growth of large language models (LLMs) has transformed natural language processing, enabling the creation of text that is almost close to human writing. However, the increasing integration of AI-generated content has raised serious ethical challenges, particularly when we talk about the attribution of moral duty. The questions arise about accountability for misinformation, bias, and harmful outputs because LLMs operate without true agency or intent. This study critically examines the ethical paradox of AI-generated texts. It explores the roles and responsibilities of developers, users, and policymakers in mitigating risks associated with generative models. The study emphasizes the need for ethical frameworks that make fairness, transparency, and human oversight a priority. Furthermore, this research aims to contribute to current discussions on the moral and societal consequences of AI-generated language. The study offers a framework for responsible and ethically aligned AI development.