ABSTRACT

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.

摘要

本研究借鉴了有关机器生成新闻的现有文献，研究了跨文化背景下的机器生成艺术品。它结合了机器学习方法和在线实验，并研究了不同类型的艺术品和不同的作者线索如何影响参与者对机器生成的作品的开放式响应。结果表明，尽管体裁和文化影响了参与者的讨论主题和用词，但参与者对机器生成的艺术品和人类生成的艺术品的反应之间的差异并不明显。这项研究测试了机器启发式的解释能力，并证明了在未来基于AI的媒体研究中整合多种方法的可行性。