Artificial intelligence as a co-author for local media journalists: cognitive load implications in content creation

Section: Artificial Intelligence in Media and Communication Studies

The article presents a pilot study of cognitive load among local media journalists interacting with generative AI tools. The relevance of this research stems from the structural digital inequality between newsrooms: differences between national and regional media are structural rather than geographical, arising from unequal access to resources, levels of income, education, specialization, and digital competence. These factors shape the pace and quality of AI adoption and, consequently, the nature of cognitive load. Despite the growing potential of AI to automate routine tasks and support analytical work, journalists in local media face considerable challenges in mastering these technologies. The study aims to develop a conceptual framework and methodological toolkit for measuring journalists’ cognitive load when engaging with generative AI systems. At the first stage, a quasi-experiment was conducted with ten local media journalists who tested three platforms (GigaChat, DeepSeek, and @GPT4TelegramBot). The results provide a preliminary assessment of the applicability of the proposed approach and indicate directions for further research. The theoretical basis of the study is cognitive load theory, and measurement was carried out using a modified NASA-TLX scale. Findings suggest that the highest cognitive load occurs during the formulation and structuring of prompts, continuous monitoring and correction of generated text, and efforts to maintain or restore dialogue context when the system provides insufficient support. Interface constraints were found to contribute substantially to extraneous cognitive load.

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To cite this article: Pavlushkina N. A., Litvinova A. N. (2025) Iskusstvennyy intellekt kak soavtor zhurnalista lokal’nykh media: osobennosti kognitivnoy nagruzki pri sozdanii kontenta [Artificial intelligence as a co-author for local media journalists: cognitive load implications in content creation]. Vestnik Moskovskogo Universiteta. Seriya 10. Zhurnalistika 5: 104–134. DOI: 10.55959/msu.vestnik.journ.5.2025.104134