Prof. Por Lip Yee, Professor at CSNET, Universiti Malaya.
Prof. Por Lip Yee was invited as a Keynote Speaker at the 4th International Conference on Electronic Information Engineering and Data Processing (EIEDP 2025), where he delivered the keynote "The Role of Artificial Intelligence in Modern Journalism", contributing research on the growing influence of artificial intelligence in journalism. The keynote examines how AI technologies are reshaping every stage of the news lifecycle, from gathering and verification to production and distribution.
AI Enters the Newsroom
The relationship between AI and journalism has shifted from speculative to operational. In contemporary newsrooms, technologies such as natural language processing (NLP), machine learning (ML), and big data analytics are no longer experimental tools but active participants in the journalistic process. The paper surveys how these capabilities are applied across news collection, content creation, and audience distribution, providing a structured overview of both the gains and the risks involved.
What AI Does in Journalism
Automated content generation allows structured datasets, such as financial summaries, sports statistics, and election results, to be converted into readable articles without human intervention. Personalised news recommendation systems analyse individual user behaviour to curate feeds that surface stories most likely to resonate with each reader. Trend analysis tools help editorial teams identify emerging stories by monitoring social media activity, search queries, and wire services at a scale no human team could sustain. Together, these capabilities raise editorial productivity and extend the reach of news organisations significantly.
Efficiency, but at a Cost
The efficiency gains are real, but the paper does not present them uncritically. Automation of content generation raises questions about editorial accountability and the risk of publishing factual errors at scale with no human in the loop to catch them. Personalisation algorithms, while improving engagement metrics, can create filter bubbles that restrict users' exposure to perspectives outside their predicted preferences. This effect is especially pronounced for communities already underserved by mainstream media, where algorithmic curation can reinforce rather than correct existing information gaps.
Toward Inclusive AI Journalism
The paper argues that addressing these risks requires deliberate policy and design choices rather than technical fixes alone. Inclusive AI algorithms must be developed with awareness of the communities they may inadvertently exclude. Digital literacy initiatives should equip citizens to critically evaluate AI-generated content and recognise when algorithmic curation is shaping what they see. Equitable access policies must ensure that the benefits of AI-driven journalism reach all segments of society, not only those already digitally connected. These are governance questions that sit at the intersection of media policy, public education, and technology design.
The paper was presented at EIEDP 2025, the 4th International Conference on Electronic Information Engineering and Data Processing.