CfP: vol. 18, n° 2(36)/ 2025/Artificial Intelligence in Journalism and Public Relations Journalisme et relations publiques face à l’Intelligence Artificielle

Call for Papers for volume 18, n° 2(36)/ 2025

ESSACHESS – Journal for Communication Studies 

Artificial Intelligence in Journalism and Public Relations 

Journalisme et relations publiques face à l’Intelligence Artificielle 

Guest editors / Coordination

Mónika ANDOK, Pázmány Péter Catholic University, HUNGARY


András RADETZKY, Pázmány Péter Catholic University, HUNGARY


In the development of journalism and mass communication, the dominant communication technologies of the given era always had a decisive role, which later became institutionalized and brought a new period in the history of the press. Starting from the 19th century professionalization of the printing industry and its efficiency-enhancing innovations to the transformation of news gathering, from the telegraph to satellite networks (Briggs – Burke 2009, Barbier & Lavenier 2000). In the last third of the 19th century, the changes in the publishing of newspapers and the electronic textualization of press texts show many analogies with the processes associated with artificial intelligence today. While at that time a distinction was made between "electronic insider / outsider" in terms of existing or lacking journalistic skills in the field of creating media texts, today specialists talk about Artificial Intelligence literacy (Marvin 1988: 15-17). 

The efficient use of computer networks and data played an increasingly important role in the tools of journalists, and from the beginning of the 2000s, the so-called data journalism also appeared. For the high-quality cultivation of data journalism, on the one hand, finding and filtering data, and on the other hand, new types of storytelling and visualization belong to the basic journalistic skills (Gray, Chambers & Bounegru 2012). The next stage is the smart journalism which includes using drones or 360 footages as well as the use of artificial intelligence (Marconi 2020, Calvo-Rubio 2021, Diakopoulos 2019, Broussard, et al 2019).

Although the release of Chat GPT in the fall of 2022 really turned public interest in the direction of artificial intelligence, the possibilities and dangers of its operationalization have long been addressed in scientific literature, in many segments of society and in institutional systems (Ribeiro et al. 2021, Jiang et al. 2017, Yang et al. 2021). Within the field of Artificial Intelligence, we want to focus on generative AI. Generative artificial intelligence (generative AI) is a type of AI that can create new content and ideas, including conversations, stories, images, videos, The communication and media organizations can use generative AI for various purposes, like chatbots, media creation, and product development and design. Technically, this type of AI learns patterns from training data and generates new, unique outputs with the same statistical properties. Generative AI models use prompts to guide content generation and use transfer learning to become more proficient.

With the advent of Artificial Intelligence, several changes related to journalism can be detected. These include (1) the changes in the global media landscape, (2) the transformation of the media industry, (3) the changes taking place in the arenas of content production and sharing, and (4) the changing perceptions of the role of journalists.

 (1) In terms of the global media scene, the literature expects basically positive effects, starting from the fact that artificial intelligence makes the operation of the global media system easier and more efficient. According to a March 2023 report by Goldman Sachs, “… the widespread adoption of artificial intelligence could increase labour productivity and increase global GDP by 7% per year over a 10-year period.” (Briggs & Kodnani, 2023) However, the growth is not expected to be the same, the lag of the global south in news production, distribution, and the entire media industry will increase. North America dominated the artificial intelligence market in media and entertainment with a 39.0% share in 2021, and this proportion will increase (AI in Media & Entertainment Market Industry Outlook 2022-2032). Along with this, artificial intelligence-related education must also be provided on a global level, so that media users can effectively use the application possibilities of AI and understand the media environment operating with AI assistance.

 (2) We can summarize the expected changes at the industry level, at the level of media enterprises, as follows. According to Sahota's 2023 analysis, significant industry expansion is expected, with a compound annual growth rate (CAGR) of 31.89%, and the market value of artificial intelligence in the media and entertainment industry is forecast to reach $124.48 billion by 2028 (Sahota 2023). New business models appear in the media industry, such as more effective paywall applications such as Piano or Sophi. At the same time, the New York Times filed a lawsuit against OpenAI in 2023 for alleged copyright infringement. The publisher of the New York Times claims that millions of its articles were used without their permission to train ChatGPT (Grynbaum & Mac 2023). Meanwhile another large media conglomerate, Axel Springer, agreed with OpenAI. A recent landmark deal between the two companies will bring in tens of millions of euros a year for Axel Springer by allowing Open AI to pull content from Bild, Politico and Business Insider. According to some, this solution could also serve as a possible model for the wider industry (Axel Springer and Open AI 2023). Open AI has entered into a similar agreement with the AP news agency, based on which AP provides access to both its historical archives and new content (Newman 2024:15). But it is not only copyrights that are expected to change. The broader regulatory environment of the media industry is also changing, a process that has already begun with the adoption of the Digital Service Act in the European Union. All of this leads to the fact that in the field of journalism and the media, it becomes necessary to rethink the issues of normativity, control and review the ethical aspects (Soto-Sanfiel 2022, Gallagher 2020, Meese 2021, Mellado 2019, 2020, Nielsen & Ganter 2022, Boczkowski 2005, Gallagher 2020, Floridi 2023). Artificial intelligence also brings industrial change in the direction of content consumers, as it enables producers of media content to use more personalized offers (without language constraints).

 (3) The third major direction of changes can be predicted at the level of media content production. After all, artificial intelligence applications can help in many aspects of journalistic work. They can be used for trend monitoring, forecasting, news gathering, and data verification. Here we can mention applications such as Pinpoint AI, Tabula AI or Open Refine. The most striking and well-known applications for ordinary users are related to the creation of content. This includes translation, description (audio-text), and text/image generation. Narrativa AI, Radar AI, Amazon Polly, Trint, Chat GPT, DALL-E and Sora can be mentioned here. Journalistic work can also be assisted by artificial intelligence during editing, whether it is content summarisation, extracting or even rewriting. Such are the Agolo AI or ETX studio applications. Archive AI helps in archiving, Membrace AI and Toloka AI in moderation, while Crux AI helps in optimizing sharing and recommendation (Pavlik 2023, Dodds et al 2023, Moran, R.E., & Shaikh 2022, Bastian et al, 2021, Túñez-López et al 2021). 

(4) Finally, the changes related to artificial intelligence are also appearing at the level of journalists and media workers. Their attitudes regarding artificial intelligence are changing, based on the research so far, they see it more as a tool that helps develop creativity and increases efficiency. And only a small half of journalists think that their work could be completely replaced by artificial intelligence. The ethical aspects of use appear particularly strongly in relation to the application of artificial intelligence in the journalistic profession, this is the question that, based on the research so far, concerns the representatives of the profession the most. How will AI be authentic, how can it be accounted for and verified? How can transparency be ensured, and who bears what responsibility during its application? (Walters 2022, Sun et al 2022, Hanitzsch. 2017 Hanusch 2017, Tandoc et al 2013)

The sharing of experiences and good practices related to the use of GenAI questions of credibility and responsibility, ethical considerations[1] and the issue of development and further training play a significant role in journalistic professional considerations (Deuze, & Beckett 2022, Leiser 2022)

The special issue wants to present the ways and consequences of using artificial intelligence not only in the field of journalism, but also in other communication professions. Focusing on the field of Public Relations: how AI can be used there in crisis communication, reputation management, press analysis, predictive analytics or social media management (Swiatek, L., & Galloway 2022).

Suggested topics for the special issue:

-        Presentation of empirical research and case studies on the use of AI (gen AI) in media content production, journalistic and editorial work

-       Presentation of empirical research and case studies on the application of artificial intelligence and gen AI in public relations agencies.

-       Comprehensive analyzes of content generation in relation to communication professions.

-       Emergence of new business models related to Artificial Intelligence applications

-       Ethical questions regarding the use of artificial intelligence in journalism.

-       Ethical questions regarding the use of artificial intelligence in Public Relations.

-       New journalistic role perceptions and attitudes regarding artificial intelligence

-       New role perceptions and attitudes regarding artificial intelligence in PR professions.

-       Analytical presentation of educational programs for the use of artificial intelligence in the field of journalism.

-       Analytical presentation of educational programs for the use of artificial intelligence in the field of PR professions.

Important Deadlines

-       November 1st, 2024: submission of the proposal in the form of an extended abstract of maximum 2 pages. The proposal must include a list of recent references and 5 keywords.

-       December 15, 2024: acceptance of the proposal.

-       March 5, 2025: full paper submission.

-       June 15, 2025: reviewer’s comments to be communicated to authors.

-       July 25, 2025: submission of paper with final revisions (after revisions).

-       December 2025: journal publication.

Full papers should be between 6,000-8,000 words in length. Papers can be submitted in English or French. The abstracts should be in English and French (150-200 words) followed by 5 keywords. Please provide the full names, affiliations, and e-mail addresses of all authors, indicating the contact author. Papers, and any queries, should be sent to:

Authors of the accepted papers will be notified by e-mail.


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Hanitzsch, Th. 2017. Professional identity and roles of journalists. In Oxford Research Encyclopedia of Communication. Oxford: Oxford University Press

Hanusch, F. 2017. “Web Analytics and the Functional Differentiation of Journalism Cultures: Individual, Organizational and Platform-Specific Influences on Newswork.” Information, Communication & Society 20 (10): 1571–1586.

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Meese, J., & Hurcombe, E. (2021). Facebook, news media and platform dependency: The institutional impacts of news distribution on social platforms. New Media & Society, 23(8), 2367-2384.

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Newman, N. (2024). Journalism, media and technology trends and predictions 2024. Reuters Institute for the Study of Journalism

Nielsen, R. K., and S. A. Ganter. 2022. The Power of Platforms: Shaping Media and Society. Oxford University Press.

Pavlik, J. V. (2023). Collaborating with ChatGPT: Considering the implications of generative artificial intelligence for journalism and media education. Journalism & Mass Communication Educator, 78(1), 84-93.

Ribeiro, J., Lima, R., Eckhardt, T., & Paiva, S. (2021). Robotic process automation and artificial intelligence in industry 4.0–a literature review. Procedia Computer Science181, 51-58.

Soto-Sanfiel, M. T., Ibiti, A., Machado, M., Marín Ochoa, B. E., Mendoza Michilot, M., Rosell Arce, C. G., & Angulo-Brunet, A. (2022). In search of the Global South: assessing attitudes of Latin American journalists to artificial intelligence in journalism. Journalism studies, 23(10), 1197-1224.

Sun, M., Hu, W., & Wu, Y. (2022). Public perceptions and attitudes towards the application of artificial intelligence in journalism: From a China-based survey. Journalism Practice, 1-23.

Swiatek, L., & Galloway, C. (2022). Artificial intelligence and public relations: Growing opportunities, questions, and concerns. In The Routledge Companion to Public Relations (pp. 352-362). Routledge.

Tandoc, Edson, Lea Hellmueller, and Tim Vos. 2013. Mind the Gap: Between Role Conception and Role Enactment. Journalism Practice 7: 539–54

Túñez-López, J. M., Fieiras-Ceide, C., & Vaz-Álvarez, M. (2021). Impact of Artificial Intelligence on Journalism: transformations in the company, products, contents and professional profile. Communication & society, 34(1), 177-193.

Walters, P. 2022. “Reclaiming Control: How Journalists Embrace Social Media Logics While Defending Journalistic Values.” Digital Journalism 10 (9): 1482–1501.

Yang, S. J., Ogata, H., Matsui, T., & Chen, N. S. (2021). Human-centred artificial intelligence in education: Seeing the invisible through the visible. Computers and Education: Artificial Intelligence2, 100008.



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