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Drawing from prior literature on machine-generated news, this study examines machine-generated artworks in a cross-cultural context. It combines machine learning approaches with online experiments and investigates how different genres of artworks and different authorship cues influence participants’ open-ended responses to machine-generated works. Results suggest that while genres and cultures affected participants’ discussion topics and word use, the differences between participants’ responses to machine-generated artworks and human-generated ones were not evident. This study tests the explanatory power of machine heuristic and demonstrates the feasibility of integrating multiple methods in future AI-based media research.
Xu et al. (Thu,) studied this question.