Abstract
Abstract Generative AI has become part of contemporary artistic practice, enabling the creation of texts, images, music, and audiovisual works through processes of variation, recombination, and transformation. As AI-generated outputs increasingly resemble existing works, disputes have intensified over how such creative connections should be understood and governed. Much of the current copyright debate approaches these questions through the lens of reproduction, focusing on copying during AI training or in the process of generating outputs. This emphasis leaves an important gap: how to evaluate creative reliance that is non-literal, indirect, and difficult to trace to specific technical processes. This article addresses that gap by revisiting the copyright framework governing adaptations and derivative works. Rather than treating copyright doctrine as a fixed set of rules, the analysis approaches it as an evolving conceptual framework shaped by changing modes of cultural production. By examining the historical development of the adaptation right, its implementation across jurisdictions, and its relationship to the principle that copyright protects expression rather than ideas, the article highlights its potential to govern forms of creative transformation that fall between copying and independent creation. Building on this insight, the article proposes an output-oriented enquiry based on “substantial recognisable linkage,” asking whether an AI-generated work can reasonably be perceived as drawing on protectable expression in a prior work, rather than merely reflecting shared styles, genres, or ideas. Focusing on the observable qualities of AI-generated outputs as they are perceived in their cultural context, this approach offers a conceptual vocabulary aligned with creative practices such as remix, variation, and stylistic exploration. At the same time, the article emphasises that any broader reliance on adaptation-based protection must be accompanied by robust exceptions and limitations, in order to preserve artistic experimentation, cultural exchange, and freedom of expression in AI-mediated creative environments.