Research Article

The Transformation of Journalism in the Era of Artificial Intelligence and Practitioners’ Perspectives on Human-Machine Interaction

Jiapeng ChenSchool of Journalism and Communication, Sun Yat-sen University, Guangzhou, China*

* Corresponding author: [email protected]

Abstract

In recent years, generative artificial intelligence (AI) has been applied in various fields of journalism. As AI is involved in news generation, it inevitably affects the existing landscape of the industry. Technological characteristics of AI and the interaction process between practitioners and AI are important factors affecting the development of the industry in the context of AI-driven transformation. Therefore, this paper explores how generative AI impacts the operation of news organizations as well as how journalists perceive AI and its impact on news production through human-machine interactions. The results show that AI enhances the efficiency of news production and distribution significantly. Nevertheless, practitioners believe that AI-generated news has not yet reached professional standards and still requires human review and verification. Meanwhile, the use of AI in journalism has prompted a role shift among practitioners, moving the focus from production to verification. Practitioners need to use AI to enhance their professional capabilities, especially in terms of innovation and creativity that AI still lacks. The ideal relationship between journalists and AI is a collaborative one, in which humans take the initiative to leverage AI’s efficiency advantages while upholding journalistic ethics and fostering innovation within the industry.

Keywords: Journalistic Transformation; Journalism Practitioners; Generative Artificial Intelligence; Actor-Network Theory; Human-Machine Interaction
Published: June 13, 2025
DOI: 10.54254/2753-7064/2025.BO23974
Volume: CHR Vol.67
pp. 153-158
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References

  1. Latour, B. (1996). On actor-network theory: A few clarifications. Soziale Welt, 47, 369-381.
  2. Stalph, F. (2019). Hybrids, materiality, and black boxes: Concepts of actor-network theory in data journalism research. Sociology Compass, 13(11), e12738. https://doi.org/10.1111/soc4.12738
  3. Jovanovic, M., & Campbell, M. (2022). Generative artificial intelligence: Trends and prospects. Computer, 55(10), 107-112. https://doi.org/10.1109/MC.2022.3192720
  4. Opdahl, A.L., et al. (2023). Trustworthy journalism through AI. Data & Knowledge Engineering, 146, 102182.
  5. Shi, Y., & Sun, L. (2024). How generative AI is transforming journalism: Development, application and ethics. Journalism and Media, 5(2), 582-594. https://doi.org/10.3390/journalmedia5020039
  6. Diakopoulos, N. (2019). Automating the news: How algorithms are rewriting the media. Harvard University Press.
  7. Stray, J. (2021). Making artificial intelligence work for investigative journalism. Algorithms, Automation, and News, 97-118. https://doi.org/10.4324/9781003045693-7
  8. Noain Sánchez, A. (2022). Addressing the Impact of Artificial Intelligence on Journalism: The perception of experts, journalists and academics. https://core.ac.uk/works/125063576/
  9. Oksymets, V. (2024). The impact of artificial intelligence on journalism practices and content creation. Vytautas Magnus University.
  10. Patrick, J. (2023). How does the conversation between a journalist and Bard, the AI chatbot at Google occur? https://www.heartofhollywoodmagazine.com/post/how-does-the-conversation-between-a-journalist-and-bard-the-ai-chatbot-at-google-occur
  11. Coddington, M. (2015). Clarifying journalism’s quantitative turn: A typology for evaluating data journalism, computational journalism, and computer-assisted reporting. Digital Journalism, 3(3):331-348.
  12. Simon, F. (2024). Artificial intelligence in the news: How AI retools, rationalizes, and reshapes journalism and the public arena.
  13. Wölker, A., & Powell, T.E. (2021). Algorithms in the newsroom? News readers’ perceived credibility and selection of automated journalism. Journalism, 22(1), 86-103. https://doi.org/10.1177/1464884918757072
  14. Ali, W., & Hassoun, M. (2019). Artificial intelligence and automated journalism: Contemporary challenges and new opportunities. International Journal of Media, Journalism and Mass Communications, 5(1), 40-49.
  15. Caliskan, A., Bryson, J.J., & Narayanan, A. (2017). Semantics derived automatically from language corpora contain human-like biases. Science, 356(6334), 183-186. https://doi.org/10.1126/science.aal4230
  16. Tejedor, S., & Vila, P. (2021). Exo journalism: A conceptual approach to a hybrid formula between journalism and artificial intelligence. Journalism and Media, 2(4), 830-840. https://doi.org/10.3390/journalmedia2040048
  17. Varian, H.R. (2018). Artificial intelligence, economics, and industrial organization (Working Paper No. 24839). National Bureau of Economic Research.
  18. Moravec, V., et al. (2024). Human or machine? The perception of artificial intelligence in journalism, its socio-economic conditions, and technological developments toward the digital future. Technological Forecasting and Social Change, 200, 123162. https://doi.org/10.1016/j.techfore.2023.123162
  19. Kothari, A., & Hickerson, A. (2020). Challenges for journalism education in the era of automation. Media Practice and Education, 21(3), 212-228. https://doi.org/10.1080/25741136.2020.1831913