African Journalism Studies

Decolonizing the Ethics of Artificial Intelligence in Journalism: Perspectives from Asia and Africa

Call for papers

Artificial Intelligence (AI) is increasingly shaping the way news is produced, distributed, and consumed across the globe (Cools & Diakopoulos, 2026). However, prevailing AI ethics frameworks are predominantly shaped by Western epistemologies, often overlooking the cultural, historical, and socio-political contexts of non-Western societies. A decolonial approach to AI ethics in journalism focuses on local knowledge systems, challenges epistemic dominance, amplifies marginalized voices, and challenges global inequalities in media representation and algorithmic power. It strengthens journalism practices that empower communities rather than reinforce global inequalities. There are multi-facet ethical challenges driven by AI journalism in the Asian and African news media landscapes.

The issue of epistemic bias and knowledge erasure calls for closer scrutiny. AI systems trained predominantly on Western data sets may misrepresent or marginalize local cultures, languages, and perspectives (Munoriyarwa, 2024). AI systems are typically trained on datasets reflecting Western languages, narratives, and cultural assumptions. In African and Asian contexts, this can lead to the marginalization of indigenous languages, oral histories, and alternative forms of storytelling. Decolonial ethics demands that AI tools recognize and integrate diverse epistemologies, ensuring that local realities are represented faithfully and respectfully in the news content.

Algorithmic inequity and media representation is concerning given automated news curation and content recommendation often prioritize sensationalist or dominant narratives (Nygren, et al 2026). For African and Asian journalists, this can mean underrepresentation of local issues or communities. Ethical AI must counter these inequities by embedding local perspectives and community feedback loops into its design, preventing algorithmic reinforcement of colonial power dynamics. In Africa, for instance, AI-driven news recommendation algorithms can prioritize global stories over local issues, limiting the visibility of important socio-political developments. Similarly, in Asia, AI tools might reinforce stereotypes or overlook minority communities due to skewed training data.

Another major ethical concerns in both regions is algorithmic bias (Tshuma & Matsilele, 2025). AI systems trained predominantly on Western data sets may misrepresent or marginalize local cultures, languages, and perspectives (Munoriyarwa, 2024). In Africa, for instance, AI-driven news recommendation algorithms can prioritize global stories over local issues, limiting the visibility of important socio-political developments. Similarly, in Asia, AI tools might reinforce stereotypes or overlook minority communities due to skewed training data. This invokes to analyze the ‘contextualized fairness’ the objectivity of AI-generated news content.  

AI-driven content generation and automated news dissemination can also amplify misinformation. In both continents, where literacy rates and digital media regulation vary widely, the rapid spread of AI-generated fake news poses a significant ethical dilemma. The ability of AI to create deepfakes or fabricate credible-looking stories makes the responsibility of news organizations and regulators even more pressing. AI in news media often relies on analyzing large amounts of user data for personalized content and targeted advertising (Gao et al, 2023). This raises ethical concerns regarding consent, data privacy, and surveillance. A decolonial approach to AI ethics calls for ensuring transparency and accountability that can ensure local regulatory frameworks for fact-checking, disclosure of AI usage and sources, information integrity and allowing communities to contest AI misrepresentation or algorithmic errors.

Moreover, the Western frameworks of AI ethics may conflict with local cultural norms, political realities, or journalistic traditions. It is crucial to recognize that AI - driven journalism can possibly ignore local histories, political struggles, or indigenous knowledge risks reinforcing epistemic colonization. Also, the issues of privacy, public interest, and storytelling ethics differ widely across Asian and African societies. Therefore, a closer scrutiny of contextual AI ethics in journalism is necessary.

A decolonial perspective on AI ethics in journalism challenges the dominance of Western frameworks and foregrounds local knowledge, voices, and realities. In African and Asian contexts, this approach ensures that AI serves as a tool for journalists’ empowerment rather than a mechanism for erasure or bias. By embracing pluralism, equity, and cultural sensitivity, journalism can leverage AI responsibly while advancing inclusive, representative, and ethically grounded media ecosystems. Hence, this special issue welcomes submissions covering the following topics:

1.     Epistemic erasure and AI Knowledge Hierarchies in Journalism.

2.     Decolonization of AI-driven news narratives, frames and discourses.  

3.     Algorithmic inequity, Visibility and representation in in Digital Journalism

4.     Transparency, accountability and AI governance in newsrooms

5.     Cultural, Linguistic, and Contextual Sensitivities in AI Journalism

6.     AI, Journalistic Labor, and Newsroom Transformation

7.     Misinformation, Information Integrity and AI

8.     Platform Power, Data Colonialism, and AI Infrastructures

9.     Public Interest Journalism and AI Futures in Africa and Asia