Kun Xu Co-Authors Article on Using Machine Learning to Learn Machines
Kun Xu, University of Florida College of Journalism and Communications Telecommunication assistant professor in emerging media, is the co-author of “Using Machine Learning to Learn Machines: A Cross-Cultural Study of Users’ Responses to Machine-Generated Artworks” published in the Journal of Broadcasting & Electronic Media on Dec. 9.
Xu, CJC doctoral student Fanjue Liu, Yi Mou, Shanghai Jiao Tong University doctoral student Yuheng Wu, Jing Zeng and Mike Schafer examined machine-generated artworks in a cross-cultural context. They combined machine learning approaches with online experiments to investigate how different genres of artworks and different authorship cues influence participants’ open-ended responses to machine-generated works.
According to the authors, “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.”