Selective Visibility of Western Media: A Critical Discourse Analysis of AI’s Responses on the Palestine and Ukraine Conflicts
Year: 2025
Type: article
Abstract: This study investigates how artificial intelligence (AI) discerns and reproduces the patterns of selective visibility in Western media coverage of two major global conflicts: Palestine–Israel and Russia–Ukraine. The primary aim is to examine how a large language model (LLM) interprets and evaluates Western media discourse through its generated responses. Employing a qualitative textual analysis, AI-generated outputs were treated as the primary data. A purposive set of prompts was submitted to the model, and the responses were analyzed using the theoretical framework of Critical Discourse Analysis (CDA). The analysis was guided by four central CDA concepts: power and ideology, lexical choice and agency, silences and foregrounding, and recontextualization. The findings demonstrate that AI is capable of identifying asymmetries in Western media representation. It exposes double standards in the framing of casualties, recognizes silences surrounding occupation and blockade, yet often mirrors agent-erasing language when describing Palestinian deaths, while employing more emotive and agentive expressions for Ukrainian and Israeli victims. Furthermore, its recontextualization of narratives frames the Palestinian struggle predominantly through security discourse, whereas Ukrainian resistance is depicted as a matter of sovereignty and heroism. The study concludes that while AI can critically engage with ideological patterns in media discourse, it simultaneously reflects the biases embedded within dominant Western epistemologies. Future research could extend this inquiry to multilingual datasets, different model versions, and diverse geopolitical contexts to assess the persistence and transformation of these discursive asymmetries.
Source: AL-ĪMĀN Research Journal
Authors: Zumer Rubab*, Sajad Ali, Aimen Khan
Institutions: Federal Urdu University, University of the West of Scotland
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4414901916