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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM44669
Volume:
9 |
4 |
Apr 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
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.
In the unfolding digital era, journalism and new media are witnessing a significant transformation, primarily driven by the emergence of Artificial Intelligence (AI). From content creation to news dissemination and audience engagement, AI technologies are gradually becoming an integral part of the media ecosystem. This research paper seeks to delve into this evolving scenario, shedding light on the dual nature of AI’s impact—its potential to revolutionise the media landscape while also posing pressing ethical questions. One of the most debated concerns surrounding the adoption of AI in journalism is algorithmic bias. Since AI models are trained on large volumes of historical data, they may unknowingly inherit and even amplify existing societal prejudices. This can lead to skewed narratives, underrepresentation of marginalised communities, and reinforcement of harmful stereotypes. For instance, if an AI system is trained predominantly on media that casts a specific community in a negative frame, it might continue to generate content that echoes the same bias, resulting in a cycle of misinformation and partiality. Another vital aspect is the lack of transparency and accountability in AI-driven journalism. Readers have a fundamental right to know how and by whom a news piece is curated. When algorithms are used to write news articles or curate personalised feeds, there must be clear disclosure about their involvement. The absence of such transparency could erode public trust, leading to growing scepticism towards mainstream news platforms, especially if audiences later realise the content they believed to be human-generated was entirely produced by machines.
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Publication Date
4/16/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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