Expert Eyes, Machine Hands: Creativity, Aesthetics, and Accountability in GenAI

Abstract

[Introduction] Generative artificial intelligence (GenAI) has become one of the defining cultural technologies of the 2020s, transforming not only how content is produced but also how creativity itself is imagined. From text generation to image synthesis, GenAI blurs distinctions between professional and amateur practice, art and automation, originality and imitation. These shifts reach far beyond the studio or agency: they unsettle cultural hierarchies, redistribute expertise, and reconfigure what it means to author or evaluate creative work with scholars and practitioners highlighting both GenAI’s disruptive and enabling potential (Amankwah-Amoah et al.; Coffin; Hartmann et al.; Matthews et al.). As such, GenAI sits squarely at the intersection of technology and culture, making it vital to examine how creative practitioners experience and negotiate its affordances. These questions mirror broader cultural discussions about automation, expertise, aesthetics, and creativity in digital media, situating our research within contemporary debates about creativity in an algorithmic age.

This article explores those negotiations through a collaborative autoethnography (Chang) in which creative professionals who are also educators worked with GenAI tools to develop an advertising campaign from concept to final artefact. By grounding our analysis in lived experience, we examine not only what GenAI can produce, but how it alters the creative process. Drawing on Csikszentmihalyi’s systems model of creativity and Bourdieu’s account of cultural capital, we situate our reflections within a wider theoretical conversation about expertise, taste, and technological mediation. These frameworks allow us to interrogate how GenAI participation affects the balance between human judgment and machine generation or between creative flow and algorithmic patterning. In doing so, we contribute to broader debates on the cultural implications of GenAI by identifying how expert practitioners sustain, redefine, and sometimes resist aesthetic standards in an era of algorithmic co-creation.