The rise of generative artificial intelligence (AI) has transformed the way creative content is produced, blurring the lines between human and machine-generated works. AI-powered systems such as ChatGPT, Stable Diffusion, and GitHub Copilot can generate text, images, music, and code that closely resemble human-created content. While these advancements offer new opportunities for innovation, they also present significant legal and ethical challenges, particularly concerning copyright and intellectual property (IP) laws.
This paper explores the legal gaps in existing copyright frameworks regarding AI-generated content, focusing on critical issues such as authorship, ownership, and infringement. As AI models are often trained on vast datasets that may contain copyrighted works, concerns about unauthorized use, data scraping, and fair use principles have led to high-profile lawsuits and regulatory debates. Additionally, jurisdictional inconsistencies further complicate the enforcement of copyright laws, as different legal systems interpret AI authorship and liability in varying ways.
Given these complexities, this research aims to analyse the shortcomings of current IP laws and assess how they can be reformed to address the evolving landscape of AI-driven creativity. The paper will examine ongoing legal cases, legislative efforts, and emerging proposals for adapting copyright laws to ensure a balance between fostering AI innovation and protecting the rights of human creators. By addressing these challenges, this study seeks to contribute to the broader discussion on AI and copyright law, advocating for clearer and more effective legal frameworks in the digital era.
