AI and politics: Do political ideologies influence people's views on AI?
Vol.18,No.1(2025)
Discourse and Interaction
Ronnakrit Rangsarittikun
Richard Watson Todd
Stephen Louw
Generative artificial intelligence (AI), with its potential to disrupt several industries, including the art industry, has been a controversial subject of discussion in mainstream newspapers. To understand the impact of political ideologies on this controversy, this study compares concerns about AI-generated art between liberals and conservatives. Data comprised comments of readers of the Daily Mail and the Guardian on a news story about an award-winning AI artwork at the Colorado State Fair, a topic that has stirred up controversies over various AI-related issues. Keyword analysis was conducted to indicate the overall concerns and to identify similarities and differences in opinions between the readers of both newspapers. A thematic analysis was then performed, and the frequencies of each theme within the two data sets were also examined to highlight the perspectives of each group of readers. Overall, in contrast to much existing literature, the findings indicate that the similarities noticeably outweigh the differences, and the differences are not immediately relevant to AI. Instead, the readers used the topic of AI as a segue to talk about other concerns, suggesting that political beliefs about AI are not yet entrenched.
Generative AI; Art; Political beliefs; Midjourney; Attitudes; Newspapers
Ronnakrit Rangsarittikun
King Mongkut's University of Technology Thonburi
Ronnakrit Rangsarittikun is Assistant Professor at King Mongkut’s University of Technology Thonburi, where he teaches English to undergraduate students. His research interests are innovation in language teaching, corpus linguistics, and language ideologies.
Richard Watson Todd
King Mongkut's University of Technology Thonburi
Richard Watson Todd is Associate Professor at King Mongkut’s University of Technology Thonburi. He has a Ph.D. from the University of Liverpool. He is the author of numerous articles and several books, including Discourse Topics (John Benjamins, 2016). His research interests include text linguistics, corpus linguistics, and educational innovations.
Stephen Louw
Westgate International School
Stephen Louw is the academic director at Westgate International School, Siem Reap, Cambodia. He holds a PhD in Applied Linguistics and has been a teacher of English for nearly 35 years. His research interests include teacher education and school management.
Adajian, T. (2024). The definition of art. In E. N. Zalta & U. Nodelman (Eds.), The Stanford encyclopedia of philosophy (Fall 2024 Edition). Retrieved from https://plato.stanford.edu/archives/fall2024/entries/art-definition/
Anthony, L. (2019). AntConc (Version 3.5.8) [Computer software].
Bellaiche, L., Shahi, R., Turpin, M. H., Ragnhildstveit, A., Sprockett, S., Barr, N., Christensen, A., & Seli, P. (2023). Humans versus AI: Whether and why we prefer human-created compared to AI-created artwork. Cognitive Research: Principles and Implications, 8(1), 42. https://doi.org/10.1186/s41235-023-00499-6
Biswal, S. K., & Gouda, N. K. (2020). Artificial intelligence in journalism: A boon or bane? In A. J. Kulkarni & S. C. Satapathy (Eds.), Optimization in machine learning and applications (pp. 155–167). Springer. https://doi.org/10.1007/978-981-15-0994-0
Carl, N., Richards, L., & Heath, A. (2019). Preference for realistic art predicts support for Brexit. The British Journal of Sociology, 70(4), 1128–1134. https://doi.org/10.1111/1468-4446.12489
Castelo, N., & Ward, A. F. (2021). Conservatism predicts aversion to consequential artificial intelligence. PLOS One, 16(12), 1–19. https://doi.org/10.1371/journal.pone.0261467
Chamorro‐Premuzic, T., Reimers, S., Hsu, A., & Ahmetoglu, G. (2009). Who art thou? Personality predictors of artistic preferences in a large UK sample: The importance of openness. British Journal of Psychology, 100(3), 501–516. https://doi.org/10.1348/000712608X366867
Childress, C. C., & Friedkin, N. E. (2012). Cultural reception and production: The social construction of meaning in book clubs. American Sociological Review, 77(1), 45–68. https://doi.org/10.1177/0003122411428153
Csikszentmihalyi, M. (1997). Flow and the psychology of discovery and invention.Harper Perennial. Retrieved from https://www.rochester.edu/warner/lida/wp-contentuploads/2022/11/creativity-by-mihaly-csikszentmihalyi.pdf
de Burgh, H. (2008). Journalism with attitude: The Daily Mail. In H. de Burgh & P. Lashmar (Eds.), Investigative Journalism (pp. 283–299). Routledge.
Delannoy, B. (2019). The dismantling of the ‘Jungle’ of Calais in October 2016: A critical discourse analysis of the Daily Mail and The Guardian [Master’s thesis]. Université de Liège.
Demata, M., Conoscenti, M., & Stavrakakis, Y. (2020). Riding the populist wave: Metaphors of populism and anti-populism in the Daily Mail and The Guardian. Iperstoria, 15, 8–35. https://dx.doi.org/10.13136/2281-4582/2020.i15.686
Ekstrom, P. D., & Federico, C. M. (2019). Personality and political preferences over time: Evidence from a multiwave longitudinal study. Journal of Personality, 87(2), 398–412. https://doi.org/10.1111/jopy.12398
Feist, G. J., & Brady, T. R. (2004). Openness to experience, non-conformity, and the preference for abstract art. Empirical Studies of the Arts, 22(1), 77–89. https://doi.org/10.2190/Y7CA-TBY6-V7LR-76GK
Gangadharbatla, H. (2022). The role of AI attribution knowledge in the evaluation of artwork. Empirical Studies of the Arts, 40(2), 125–142. https://doi.org/10.1177/0276237421994697
Garcia, M. B. (2024). The paradox of artificial creativity: Challenges and opportunities of generative AI artistry. Creativity Research Journal, 1–14. https://doi.org/10.1080/10400419.2024.2354622
Gates, B. (2023). The age of AI has begun. Gates Notes. Retrieved May 2024, from https://www.gatesnotes.com/The-Age-of-AI-Has-Begun
Greenberg, C. (2000). Homemade esthetics: Observations on art and taste. Oxford University Press.
Gu, L., & Li, Y. (2022). Who made the paintings: Artists or artificial intelligence? The effects of identity on liking and purchase intention. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.941163
Jiang, H. H., Brown, L., Cheng, J., Khan, M., Gupta, A., Workman, D., & Gebru, T. (2023). AI art and its impact on artists. In F. Rossi, S. Das, J. Davis, K. Firth-Butterfield, & A. J. London (Eds.), Proceedings of the 2023 AAAI/ACM conference on AI, ethics, and society (pp. 363–374). Association for Computing Machinery. https://doi.org/10.1145/3600211.3604681
Köbis, N., & Mossink, L. D. (2021). Artificial intelligence versus Maya Angelou: Experimental evidence that people cannot differentiate AI-generated from humanwritten poetry. Computers in Human Behavior, 114, 1–13. https://doi.org/10.1016/j.chb.2020.106553
Lee, T., Yasunaga, M., Meng, C., Mai, Y., Park, J. S., Gupta, A., & Liang, P. (2023). Holistic evaluation of text-to-image models. Retrieved from arXiv preprint arXiv:2311.04287.
Makridakis, S. (2017). The forthcoming artificial intelligence (AI) revolution: Its impact on society and firms. Futures, 90, 46–60. https://doi.org/10.1016/j.futures.2017.03.006
Matthews, B., Shannon, B., & Roxburgh, M. (2023). Destroy all humans: The dematerialisation of the designer in an age of automation and its impact on graphic design – A literature review. International Journal of Art & Design Education, 42(3), 367–383. https://doi.org/10.1111/jade.12460
Millet, K., Buehler, F., Du, G., & Kokkoris, M. D. (2023). Defending humankind: Anthropocentric bias in the appreciation of AI art. Computers in Human Behavior, 143 ,107707. https://doi.org/10.1016/j.chb.2023.107707
Mirbabaie, M., Brünker, F., Möllmann, N. R., & Stieglitz, S. (2022). The rise of artificial
intelligence – Understanding the AI identity threat at the workplace. Electronic Markets, 1–27. https://doi.org/10.1007/s12525-021-00496-x
Onwuegbuzie, A. J., & Leech, N. L. (2006). Linking research questions to mixed methods data analysis procedures. The Qualitative Report, 11(3), 474–498.
Oppenlaender, J. (2022). The creativity of text-to-image generation. In M. Scheutz, R. Calo, M. Mara, & A. Zimmermann (Eds.), Proceedings of the 25th international academic Mindtrek conference (pp. 192–202). Association for Computing Machinery. https://doi.org/10.1145/3569219.3569352
Oppenlaender, J. (2023). A taxonomy of prompt modifiers for text-to-image generation. Behaviour & Information Technology, 1–14. https://doi.org/10.1080/0144929X.2023.2286532
Pojanapunya, P., & Watson Todd, R. (2018). Log-likelihood and odds ratio: Keyness statistics for different purposes of keyword analysis. Corpus Linguistics and Linguistic Theory, 14(1), 133–167. https://doi.org/10.1515/cllt-2015-0030
Roe, J., & Perkins, M. (2023). ‘What they’re not telling you about ChatGPT’: Exploring the discourse of AI in UK news media headlines. Humanities and Social Sciences Communications, 10(1), 1–9. https://doi.org/10.1057/s41599-023-02282-w
Scott, M., & Tribble, C. (2006). Textual patterns: Key words and corpus analysis in language education. John Benjamins.
Thurman, N., & Fletcher, R. (2019). Has digital distribution rejuvenated readership? Revisiting the age demographics of newspaper consumption. Journalism Studies, 20(4), 542–562. https://doi.org/10.1080/1461670X.2017.1397532
Topol, E. J. (2019). High-performance medicine: The convergence of human and artificialintelli gence. Nature Medicine, 25(1), 44–56. https://doi.org/10.1038/s41591-018-0300-7
Vaccari, C., & Chadwick, A. (2020). Deepfakes and disinformation: Exploring the impact of synthetic political video on deception, uncertainty, and trust in news. Social Media+ Society, 6(1). https://doi.org/10.1177/2056305120903408
Watson Todd, R. (2023). Crowdsourcing research topics to raise public understanding of applied linguistics. Qeios. https://doi.org/10.32388/XDN1K2
Wilson, G. D., Ausman, J., & Mathews, T. R. (1973). Conservatism and art preferences. Journal of Personality and Social Psychology, 25(2), 286. https://doi.org/10.1037/h0033972
Zenner, S. (2020). What informs our visual taste? The impact of personality and political on visual preferences [Doctoral dissertation]. The University of North Carolina at Chapel Hill.
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Copyright © 2025 Ronnakrit Rangsarittikun, Richard Watson Todd, Stephen Louw