What Makes Creation Human? Authorship, Reasons, and Meaningful Human Control in Generative AI

• URL: http://arxiv.org/abs/2609.10738v1
• Date: Wed, 09 Sep 2026 18:32:42 GMT
• Title: What Makes Creation Human? Authorship, Reasons, and Meaningful Human Control in Generative AI
• Abstract summary: This paper distinguishes creativity at the level of the work from creative agency at the level of the creator.<n>It argues that human authorship cannot be determined solely by manual intervention, degree of automation, the origin of an initial idea, or final selection authority.<n>The paper proposes dynamic-reflexive tracking (DRT), which requires that a creator's evolving reasons undergo reflective uptake.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Generative artificial intelligence (GenAI) significantly expands creators' productive capacity, but this does not necessarily entail a corresponding increase in creative agency or authorship. This paper distinguishes creativity at the level of the work from creative agency at the level of the creator, and argues that human authorship cannot be determined solely by manual intervention, degree of automation, the origin of an initial idea, or final selection authority. Rather, authorship depends on whether human judgment and reasons genuinely shape the development of the work. To articulate this requirement, the paper introduces Meaningful Human Control (MHC) into generative creation and identifies a limitation of its classical tracking condition. Creative reasons are not always fully specified prior to interaction with AI; they may emerge, change, or be abandoned as the creative process unfolds. The paper therefore proposes dynamic-reflexive tracking (DRT), which requires that a creator's evolving reasons undergo reflective uptake, exert genuine influence on the subsequent trajectory of creation, and remain capable of rejecting and redirecting the system's default direction. DRT consists of four conditions: diachronic reason formation, reflective uptake, trajectory efficacy, and contestability and redirection, together with a minimal tracing requirement. The paper argues that human authorship under generative AI depends not on how many steps a person personally performs, but on whether that person's reasons continuously, reflectively, and effectively shape what the work becomes.

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