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Paper ID:IJSREM64946

AI and Journalism Education: Opportunities and Challenges

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM64946

Volume:

10 |

6 |

Jun 2026

Pages:

1-6

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM64946

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

Asst. Prof. Jyoti Gour Verma

Asst. Prof. Jyoti Gour Verma

Social Science

Dr. C. V. Raman University, Khandwa (M.P)

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Abstract

The rapid evolution of modern digital methodologies has situated Artificial Intelligence (AI) at the absolute forefront of multiple operational domains, driving a foundational transformation in how academic instruction and professional practice are conceptualized, with journalism education serving as a primary example. AI models have introduced highly innovative protocols for data collection, deep analytical investigation, and automated information dissemination, actively challenging conventional reportorial practices and forcing an immediate reassessment of traditional learning pedagogy. By streamlining statistical interpretation, facilitating automated content engineering, diagnosing digital misinformation, and tracking real-time audience patterns, automated intelligence is fundamentally reshaping the core competencies required of contemporary journalists. This research paper aims to evaluate the multifaceted applications of algorithmic systems within mass communication programs, analyze the immediate structural constraints and ethical considerations accompanying its institutional adoption, and formulate strategic parameters for successfully embedding AI frameworks into academic syllabi. In doing so, it stresses the profound capacity of AI systems to optimize technical capabilities while training student journalists to manage the highly dynamic, modern media ecosystem with deep professional responsibility, factual precision, and operational efficiency.

KEYWORDS

Artificial Intelligence (AI) Journalism Education Data Journalism Automated Reporting Fake News Detection Media Ethics Content Curation Trend Analysis Creativity in Journalism Technical Proficiency Digital Media Future of Journalism

Cite This Article

Asst. Prof. Jyoti Gour Verma, "AI and Journalism Education: Opportunities and Challenges," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 6, pp. 1-6, Jun 2026. https://doi.org/10.55041/IJSREM64946

Full Article/Conclusion

AI is poised to play a defining role in the future of public communication. However, its success lies in being embraced as a supportive enhancement rather than a replacement for human creativity, conscience, and professional judgment. By proactively integrating AI tools into educational programs, universities can cultivate resourceful, tech-savvy journalists who contribute meaningfully to the dissemination of verified truth and democratic discourse in global society.

References

[1] 1. Carlson, M. (2015). The robotic reporter: Automated journalism and the redefinition of labor, compositional forms, and journalistic authority. Digital Journalism, 3(3), 416–431. [2] 2. Clerwall, C. (2014). Enter the robot journalist: Users’ perceptions of automated content. Journalism Practice, 8(5), 519–531. [3] 3. Deuze, M. (2017). Considering a possible future for digital journalism. Digital Journalism, 5(5), 648–654. [4] 4. Graefe, A. (2016). Guide to automated journalism. Columbia Journalism School, Tow Center for Digital Journalism. [5] 5. Lazer, D. M. J., Baum, M. A., Benkler, Y., Berinsky, A. J., Greenhill, K. M., Menczer, F., … & Zittrain, J. L. (2018). The science of fake news. Science, 359(6380), 1094–1096. [6] 6. Napoli, P. M. (2014). On automation in media industries: Integrating algorithmic media production into media industries scholarship. Media Industries Journal, 1(1). [7] 7. Pavlik, J. V. (2019). Journalism in the age of virtual reality, augmented reality, and artificial intelligence. Journalism & Mass Communication Quarterly, 96(1), 75–95. [8] 8. Pennycook, G., & Rand, D. G. (2020). Fighting misinformation on social media using crowdsourced judgments of news source quality. Proceedings of the National Academy of Sciences, 117(1), 277–283. [9] 9. Tandoc, E. C. (2019). Anatomy of an algorithmic gatekeeper: The case of the Google News algorithm. Journalism, 20(7), 925–941. [10] 10. Tandoc, E. C., Lim, Z. W., & Ling, R. (2018). Defining “fake news”. Digital Journalism, 6(2), 137–153. [11] 11. Waisbord, S. (2019). The vulnerabilities of journalism. Journalism, 20(1), 210–213.

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Publication Date

6/14/2026

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Double-Blind Peer Review

Review Rounds: 2

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