Journal of AI-Driven Communication Engineering

Special Issue: Artificial Intelligence Across the Communication Stack: Engineering, Human Interaction, and Governance in the 6G Era

Vol. 2 (2026)

Generative AI as Mediator of Interpersonal Communication: Effects on Social Dynamics, Linguistic Norms, and Relational Authenticity

DOI:
https://doi.org/10.31875/2979-1081.2026.02.09
Submitted
July 5, 2026
Published
2026-07-05

Abstract

The integration of generative artificial intelligence into everyday interpersonal communication - through AI-assisted writing, real-time translation, automated summarization, and conversational suggestion tools - represents a structural transformation in the mediation of human-human communication. Unlike earlier communication technologies that mainly transmitted or stored human-generated content, generative AI actively co-produces communicative output through a system architecture that includes user interfaces, prompt and context management, large language model inference, personalization modules, disclosure controls, and post-generation human editing. This paper examines AI-mediated interpersonal communication (AIMIC) as both a social phenomenon and an implementable communication system. It analyzes three interconnected effects: linguistic convergence, redistribution of communicative labor, and challenges to relational authenticity. The revised AIMIC framework links these effects to concrete implementation layers in email assistants, messaging platforms, translation tools, collaborative writing systems, and organizational communication software. The paper argues that responsible AIMIC design requires preserving human communicative agency, making AI involvement contextually transparent, monitoring linguistic and relational impacts, and embedding governance mechanisms into the communication pipeline. The paper concludes with practical examples, evaluation recommendations, and design principles for platform developers, educators, organizations, and policymakers.

References

  1. Anderson, B., et al. (2023). AI writing assistants and communicative labor: An empirical analysis of usage patterns and stylistic effects in professional contexts. Journal of Computer-Mediated Communication, 28(4).
  2. Baym, N. K. (2015). Personal Connections in the Digital Age (2nd ed.). Polity Press.
  3. Bereiter, C., & Scardamalia, M. (1987). The Psychology of Written Composition. Lawrence Erlbaum Associates.
  4. Crawford, K. (2021). Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. Yale University Press. https://doi.org/10.12987/9780300252392
  5. Goffman, E. (1959). The Presentation of Self in Everyday Life. Anchor Books.
  6. Guo, B., et al. (2023). How close is ChatGPT to human experts? Professional writing quality and stylistic convergence analysis. arXiv preprint arXiv:2305.01852.
  7. Hancock, J. T., Naaman, M., & Levy, K. (2020). AI-mediated communication: Definition, research agenda, and ethical considerations. Journal of Computer-Mediated Communication, 25(1), 89-100. https://doi.org/10.1093/jcmc/zmz022
  8. Hecht, M. L. (1993). 2002 - A research odyssey: Toward the development of a communication theory of identity. Communication Monographs, 60(1), 76-82. https://doi.org/10.1080/03637759309376297
  9. Herring, S. C. (2007). A faceted classification scheme for computer-mediated discourse. Language@Internet, 4(1).
  10. Innis, H. A. (1951). The Bias of Communication. University of Toronto Press.
  11. Ippolito, D., et al. (2020). Automatic detection of generated text is easiest when humans are fooled. Proceedings of ACL 2020. https://doi.org/10.18653/v1/2020.acl-main.164
  12. Jakesch, M., Hancock, J. T., & Naaman, M. (2023). Human heuristics for AI-generated language are flawed. Proceedings of the National Academy of Sciences, 120(11). https://doi.org/10.1073/pnas.2208839120
  13. Kasirzadeh, A., & Gabriel, I. (2023). In conversation with artificial intelligence: Aligning language models with human values. Philosophy & Technology, 36(2). https://doi.org/10.1007/s13347-023-00606-x
  14. McLuhan, M. (1964). Understanding Media: The Extensions of Man. McGraw-Hill.
  15. Walther, J. B. (1992). Interpersonal effects in computer-mediated interaction: A relational perspective. Communication Research, 19(1), 52-90. https://doi.org/10.1177/009365092019001003
  16. Weidinger, L., et al. (2022). Taxonomy of risks posed by language models. Proceedings of FAccT 2022. https://doi.org/10.1145/3531146.3533088