Combinatorial Capture: Generative AI and the Displacement of Transformational Creative Work
TL;DR
It is argued that current generative AI systematically favors combinatorial creativity while offering weaker support for transformational creativity, and that HCI should evaluate AI tools not only by the quality of creative outputs they enable but by the distribution of creative types they support, privilege, or suppress.
Abstract
Generative AI has intensified debate about whether technology replaces or augments human creativity. A serious treatment of this question requires distinguishing among different creative processes. Drawing on Margaret Boden’s typology of combinatorial, exploratory, and transformational creativity, together with Weisberg’s account of struggle-dependent development and Csikszentmihalyi’s systems view, I argue that current generative AI systematically favors combinatorial creativity while offering weaker support for transformational creativity. I introduce the concept of combinatorial capture to describe how AI tools pull creative work toward the forms of novelty they support best. This concept operates at several levels: as an interactional tendency, a workflow dynamic, and a socio-technical and institutional pressure. I identify three mechanisms through which combinatorial capture operates: legibility bias, uncertainty resolution, and speed asymmetry. The paper concludes by outlining a framework for transformational creativity support and argues that HCI should evaluate AI tools not only by the quality of creative outputs they enable but by the distribution of creative types they support, privilege, or suppress.
