From Search Engine to Thought Partner: Reimagining Artificial Intelligence as a New Gatekeeper in Contemporary Mass Communication — A Conceptual Framework Analysis

Authors

Dr. Roshni Kumari

Assistant Professor, Institute of Mass Communication, IPS Academy, Indore (Madhya Pradesh) (India)

Article Information

DOI: 10.47772/IJRISS.2026.100700147

Subject Category: Mass Communication

Volume/Issue: 10/7 | Page No: 2020-2033

Publication Timeline

Submitted: 2026-07-08

Accepted: 2026-07-14

Published: 2026-07-27

Abstract

Artificial Intelligence (AI) has rapidly transformed the communication landscape, extending its role far beyond simple information retrieval and automated content generation. Today, AI systems increasingly assist individuals in searching for information, generating ideas, organizing knowledge, supporting decision-making, and facilitating communication across multiple media platforms. This transformation suggests that AI is no longer functioning merely as a technological tool but is gradually emerging as a cognitive communication partner that influences how people access, interpret, and distribute information.
This conceptual paper introduces the idea of AI as a "Thought Partner" and proposes that its growing influence represents a new form of gatekeeping in mass communication. Unlike traditional media gatekeepers such as editors, journalists, and media organizations, AI systems participate directly in shaping users' information environments through personalized responses, content recommendations, language generation, and contextual assistance. Consequently, the process of communication is becoming increasingly interactive, collaborative, and algorithmically mediated.
The study adopts a qualitative conceptual research design based on analytical review and theoretical synthesis. Instead of collecting primary data, it critically examines established communication theories alongside contemporary developments in generative AI. The paper proposes a conceptual framework explaining how AI functions simultaneously as an information source, communication facilitator, cognitive assistant, and gatekeeper. The framework highlights the dynamic relationship among users, AI systems, digital platforms, and information ecosystems.
The paper further discusses the theoretical implications of AI-driven communication, including changing patterns of trust, credibility, audience participation, editorial influence, and media literacy. It argues that future communication research should move beyond understanding AI as a content-generation technology and instead recognize its expanding role in human thinking, communication processes, and knowledge construction.
The proposed framework contributes to mass communication scholarship by offering a contemporary perspective on AI-mediated communication and identifies several directions for future theoretical and empirical research.

Keywords

Artificial Intelligence, Mass Communication, Gatekeeping Theory, Thought Partner

Downloads

References

1. Castells, M. (2010). The Rise of the Network Society (2nd ed.). Wiley-Blackwell. [Google Scholar] [Crossref]

2. McQuail, D. (2010). McQuail’s Mass Communication Theory (6th ed.). Sage. [Google Scholar] [Crossref]

3. Shoemaker, P. J., & Vos, T. P. (2009). Gatekeeping Theory. Routledge. [Google Scholar] [Crossref]

4. Lippmann, W. (1922). Public Opinion. Harcourt, Brace and Company. [Google Scholar] [Crossref]

5. Katz, E., Blumler, J. G., & Gurevitch, M. (1973). Uses and Gratifications Research. Public Opinion Quarterly, 37(4), 509–523. [Google Scholar] [Crossref]

6. McCombs, M. E., & Shaw, D. L. (1972). The Agenda-Setting Function of Mass Media. Public Opinion Quarterly, 36(2), 176–187. [Google Scholar] [Crossref]

7. Sundar, S. S. (2020). Rise of Machine Agency. Journal of Computer-Mediated Communication, 25(1), 74–88. [Google Scholar] [Crossref]

8. Gillespie, T. (2014). The Relevance of Algorithms. In T. Gillespie et al. (Eds.), Media Technologies (pp. 167–194). MIT Press. [Google Scholar] [Crossref]

9. Diakopoulos, N. (2019). Automating the News. Harvard University Press. [Google Scholar] [Crossref]

10. Pavlik, J. V. (2023). Collaborating with ChatGPT. Digital Journalism, 11(5), 841–846. [Google Scholar] [Crossref]

11. Floridi, L., & Chiriatti, M. (2020). GPT-3: Its Nature, Scope, Limits, and Consequences. Minds and Machines, 30(4), 681–694. [Google Scholar] [Crossref]

12. Binns, R. (2018). Fairness in Machine Learning. Philosophy & Technology, 31(4), 543–546. [Google Scholar] [Crossref]

13. West, D. M. (2018). The Future of Work. Brookings Institution Press. [Google Scholar] [Crossref]

14. Couldry, N., & Hepp, A. (2017). The Mediated Construction of Reality. Polity Press. [Google Scholar] [Crossref]

15. Jenkins, H. (2006). Convergence Culture. NYU Press. [Google Scholar] [Crossref]

16. Turkle, S. (2011). Alone Together. Basic Books. [Google Scholar] [Crossref]

17. Napoli, P. M. (2011). Audience Evolution. Columbia University Press. [Google Scholar] [Crossref]

18. van Dijk, J. (2020). The Digital Divide. Polity Press. [Google Scholar] [Crossref]

19. Russell, S., & Norvig, P. (2021). Artificial Intelligence: A Modern Approach (4th ed.). Pearson. [Google Scholar] [Crossref]

20. UNESCO. (2023). Guidance for Generative AI in Education and Research. UNESCO. [Google Scholar] [Crossref]

Metrics

Views & Downloads

Similar Articles