Copyright Thickness, Thinness, and a Mannion Test for Images Produced by Generative Artificial Intelligence Applications


Molly Torsen Stech

Human authorship has always been, and continues to be, a foundational requirement for copyright protection to subsist in a work. Generative artificial intelligence (AI) challenges this prerequisite but does not overcome it. The output of generative AI is not discernibly different from the output of a human author and therefore benefits from a false sheen of originality. While some argue that prompt engineering fulfills the requirements of originality––the threshold for which is quite low across jurisdictions––prompting still lacks the requisite link between human creativity and the resulting work to receive copyright protections. International copyright treaties and domestic copyright law must be interpreted as aiming to provide copyright’s exclusive rights to works that reflect human originality and that reward human beings. A 2006 New York district court case outlined three means by which photographs can demonstrate originality: rendition, timing, and creation of the subject. This article proposes that each of these mechanisms, understood through the prism of generative AI, remains applicable for analyzing whether human originality subsists in a given work. Originality exists along a sliding scale, resulting in a mix of thin copyrights and thick copyrights, and everything in between. While it may not always be the case, the current relationship between generative AI and its user results in outputs that are generally too detached from the user’s creativity to satisfy the requirements of copyrightable authorship. Generative AI remixes the content on which it has been trained according to its algorithm and prompts. Human originality, however, remains the sine qua non of authorship and of copyright law.

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