Prompting Creativity: Tiered Approach to Copyright Protection for AI-Generated Content in the Digital Age

• Main Author: Jon, WooJung
• Publication Date: 2025
• Format: Article
• Language: eng
• Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
• Download full: https://doi.org/10.17645/mac.9420
• topic: AI; AI-generated content; AI prompt; copyright; creative industries; intellectual property; legal framework; prompt engineering

The rapid advancement of AI has fundamentally transformed the creative landscape, challenging traditional notions of authorship and copyright. As AI systems become increasingly capable of generating original content across diverse domains—including art, music, and literature—the legal frameworks governing intellectual property rights are struggling to keep pace. This article proposes a novel, unified, and tiered approach to copyright protection for AI prompts and AI-generated content, based on the level of human creative input required. By conducting a comprehensive analysis of legal, technical, and ethical considerations, this article explores the complex interplay among human creativity, AI technology, and intellectual property rights in the digital age. Its contributions are threefold: it conceptualizes AI prompts as potentially copyrightable works, recognizing the significant creative effort involved in their design; it develops a multifaceted framework for assessing creativity in AI prompts, addressing a critical gap in current copyright paradigms; and it proposes a tiered protection system correlating copyright scope with the degree of human creative input, offering a nuanced approach to safeguarding intellectual property in AI-generated content. This article further examines the economic and societal implications of protecting AI prompts, anticipating the emergence of new markets and professions while addressing potential abuses such as “prompt trolling.” It emphasizes the delicate balance between protecting intellectual property and fostering innovation, highlighting the importance of maintaining a robust public domain to encourage experimentation and advancement in AI technologies. The findings provide a foundation for future policy development and offer practical recommendations for implementing prompt protection and registration systems.