The emergence of Artificial intelligence (AI) technologies in human society triggers depictions of AI technologies—not only debated in hard news—but also in fictional and imagined worlds, especially the sci-fi blockbusters. These blockbusters—attracting audiences globally with fancy visual effects and popular (sometimes formulative) storytelling strategies—enable the representation of cyborgs (human-like robots) in people’s lives and shape the audience’s perception of human-machine communication. The blockbusters have been criticized as notoriously misrepresenting the role of cyborgs in human society. This project includes three parts: (1) computational analysis of the citation-networks among the movies based on digital movie achieve data; (2) a focus-group interview on the young adults as sci-fi movie audiences; and (3) a scoping review of cyborgs featured in communication journal articles. With this mixed-methods design, the current project triangulates how these sci-fi blockbusters portray cyborgs and how such portrayals are reflected in people’s way of life and scholarly research in media and communication. It advances our understanding of society’s perceptions and beliefs towards these cyborgs in particular and ethical AI and human-machine communication in general.  

Project Team

Principal Investigator: Dr. Xinzhi Zhang, Assistant Professor, Department of Interactive Media, School of Communication, Hong Kong Baptist University

Co-Investigator: Dr. Paolo Mengoni, Senior Lecturer, Department of Interactive Media, School of Communication, Hong Kong Baptist University

Website Construction and Visualization: Dr. Eric Chow, Digital Scholarship Manager, Hong Kong Baptist University Library

Data Exploration and Visualization: Ms. Yitong Gu, PhD Student, University Transdisciplinary Research Labs, School of Communication, Hong Kong Baptist University

Literature Search and Fieldwork: Ms. Rui Zhu, PhD Student, School of Communication, Hong Kong Baptist University

Data Collection and Data Analysis: Mr. Xiaohang Deng, M.Phil. student, School of Communication, Hong Kong Baptist University

Transcription and translation: Ms. Yue Hei Lam (Moon), MSc in AI and Digital Media student, School of Communication, Hong Kong Baptist University

References

Heymann, S., & Le Grand, B. (2013, July). Visual analysis of complex networks for business intelligence with Gephi. In 2013 17th International Conference on Information Visualisation (pp. 307-312). IEEE.

Radicchi, F., Castellano, C., Cecconi, F., Loreto, V., & Parisi, D. (2004). Defining and identifying communities in networks. Proceedings of the National Academy of Sciences, 101(9), 2658-2663.

Wasserman, M., Zeng, X. H. T., & Amaral, L. A. N. (2015). Cross-evaluation of metrics to estimate the significance of creative works. Proceedings of the National Academy of Sciences, 112(5), 1281-1286.

Zhang, X. & Zhu, R. (2022). Health journalists’ social media sourcing during the early outbreak of the public health emergency. Journalism Practice. Online first. doi: 10.1080/17512786.2022.2110927.

Zhang, X. & Ho, J. C. F. (2020). Exploring the fragmentation of the representation of data-driven journalism in the Twittersphere: A network analytics approach. Social Science Computer Review. Online first. doi: 10.1177/0894439320905522.

Outputs from the current project

Zhang, Xinzhi; Mengoni, Paolo (2022, Mar). Decoding the sources of creativity of cultural products: a computational method on international and Italian sci-fi movies. Public Seminar of AI and Technology in Media and Arts Talk Series, Hong Kong Baptist University and the Consulate General of Italy in Hong Kong SAR.

Zhang, Xinzhi; Zhu Rui (in review). Human-machine Communication in the Fictional World: A Scoping Review of Communication Literature. Working paper under review.

(updated: Oct 2022)