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AI and communication practices

15.03.2023 11:27 | Anonymous member (Administrator)

MedieKultur Special Issue

Theme editors: Ib T. Gulbrandsen (Associate Professor, Roskilde University), Martina S Mahnke (Associate Professor, Roskilde University), Emma Christensen (Postdoc, Roskilde University), Julie Vulpius (Postdoc, Roskilde University), and Simon Karlin (PhD Fellow, Roskilde University)

Issue editor: Martina S Mahnke (Associate Professor, Roskilde University)

Artificial intelligence (AI) is not only shaping contemporary communication processes but is actively contributing to and participating in them. Customer service chatbots communicate with us, prediction and surveillance models communicate about us, and content generators communicate instead of us. AI is, in other words, influencing how communication happens, and ultimately what it means to communicate. AI is, however, not developed, adopted, and employed in isolation. Rather, how media, researchers, citizens, vendors, data scientists, etc. understand, envision, and communicate about AI is key to how AI develops, what models are constructed, and the way they take part in processes of communication (Bailey & Barley, 2020).

The entanglement of discourse and practice, of humans and AI, raises many questions and has thus become a topic of scholarly interest across a diverse set of disciplines. While much literature has sought to define AI (see e.g., Monett & Lewis, 2018 ), such definitional work tends to neglect the significance of everyday enactments of AI; how data scientists formulate assumptions that subsequently guide their code writing, how media and vendors narrate AI to influence how citizens and potential customers imagine it, or how AI shapes communication practices in organizations. Others have discussed the potential possibilities and risks of AI, including implications for work practices, trust, as well as ethics and governance (see e.g., Crawford & Calo, 2016; Newell & Marabelli, 2018; Kellogg et al., 2020; Wiesenberg & Tench, 2020; Zuboff, 2015). However, in-depth empirical explorations, methodological and theoretical explorations of the everyday impact of how AI participates in communication and how communication participates in AI are still sparse.

This special issue aims to address this gap and invites conceptual and empirical studies that examine and reflect on the role of AI in various communication processes. We especially welcome contributions that nuance and detail the interplay between humans and AI in communication practices. The special issue assembles vital insight on AI in communication and organizing processes striving for diversity in terms of nationalities and geography among the authors as well as the theoretical perspectives and methodological approaches, such as – to mention but a few – communication, organizational, and cultural studies, science and technology studies, actor-network theory, phenomenology and qualitative and quantitative studies, action research, discourse analysis, comparative approaches, (digital) ethnography, and mixed method approaches.

Topics of interest include, but are not limited to:

  • Empirical (case) studies on the use, application, and impact of AI in communication and organizational processes
  • Studies in AI-narratives, imaginaries, and expectations about AI and its implications for communication processes
  • Studies on understanding and sense-making processes in relation to the use and implementation of AI in organizations
  • Analyses of employees’, costumer’s, individual’s or group’s conceptualizations of AI inside and outside of the traditional organizational boundaries
  • Studies of human-AI relations, for example, the ethical dimension of AI-aided decision-making, and its opportunities and challenges for AI governance
  • Critical and cultural perspectives: conflicts, tensions and negotiations of AI in organizational settings
  • New, playful, and creative ways in which AI and communication practices are intertwined 

The special issue is related to the SCAI-projekt, funded by the VELUX FOUNDATIONS:

Submission guidelines

Abstracts should contain a maximum of 500 words excluding references. It should include the research question(s) addressed, theoretical and methodological approaches as well as preliminary conclusions. Abstracts should be submitted as a Word document via our open  journal system at, where you will need to create a user account if you do not already have one. Please indicate in “comments for the editor” section that you are submitting to the special issue “AI and communication practices”. In case of any questions regarding the uploading process, please contact:


Deadline for abstract submission: May 1st, 2023

Acknowledgement of acceptance for full paper submission: May 12th, 2023

Deadline for full paper: September 11th, 2023

Notification of acceptance: November 1st, 2023

Deadline for revised articles: January 10th, 2024

Expected publication: May 2024 


Bailey, D. E. & Barley, S. R. (2020). Beyond design and use: How scholars should study intelligent technologies. Information and Organization, 30(2)

Crawford, K., & Calo, R. (2016). There is a blind spot in AI research. Nature, 538(7625), 311-313.

Kellogg, K. C., Valentine, M. A. & Christin, A. (2020). Algorithms at work: The new contested terrain of control. Academy of Management Annals, 14(1): 366-410. 

Monett, D, & Lewis, C. W. P. (2018). Getting clarity by defining Artificial Intelligence – A survey. In V. C. Müller (Ed.), Philosophy and theory of Artificial Intelligence 2017. Springer, pp. 212-214.

Newell, S. & Marabelli, M. (2018). Datafication in action. Diffusion and consequences of algorithmic decision-making. In R. D. Galliers & M.-K. Stein (Eds.), The Routledge Companion to Management Information Systems. Routledge. pp. 403-415. 

Poole, D. L. & Mackworth, A. K. (2017). Artificial intelligence: Foundations of computational agents, Oxford University Press. 

Wiesenberg, M., & Tench, R. (2020). Deep strategic mediatization: Organizational leaders' knowledge and usage of social bots in an era of disinformation. International Journal of Information Management.

Zerfass, A., Hagelstein, J., & Tench, R. (2020). Artificial intelligence in communication management: a cross-national study on adoption and knowledge, impact, challenges and risks. Journal of Communication Management, 24(4), 377-389.

Zuboff, S. (2015). Big other: Surveillance capitalism and the prospects of an information civilization. Journal of Information Technology, 30(1): 75-89.



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