Artificial intelligence has entered the journalism classroom, quietly but decisively. From automated transcription to generative writing and data analysis, AI tools are no longer futuristic add-ons; they are reshaping how journalism is taught, practised and imagined. Yet in many parts of the Global South, this technological shift is unfolding in environments marked by political pressure, uneven infrastructure and deep linguistic diversity.
A new study led by Samiya Asadi explores how journalism schools, particularly in Bangladesh, are navigating this transformation. Educators are asking difficult questions. Can AI enhance reporting without weakening critical thinking? Can innovation coexist with ethical responsibility? And how can institutions avoid importing Western technological models that may not reflect local realities?
A divided faculty and a growing student-teacher gap
One of the study’s most significant findings is a split psychology among journalism educators. On one side are educators who view AI as inevitable and essential. They argue that journalism has always adapted to technological change and that today’s journalists must master not only reporting and storytelling but also AI tools, data literacy, and algorithmic awareness. From this perspective, excluding AI from Journalism education would leave graduates unprepared for contemporary newsrooms.
On the other side are educators who remain cautious and skeptical. Their concerns are not rooted in technophobia, but in pedagogy and ethics. They worry that over-reliance on AI encourages a ‘copy-paste mindset’, weakens critical thinking, and distances students from the reflective processes that underpin good journalism, such as questioning sources, analysing power, and situating stories within social and political contexts.
Yet students are not uncritical users. Many express uncertainties about what constitutes acceptable AI use. They report a lack of clear guidelines from instructors and institutions, leaving them unsure where learning ends and misconduct begins. This confusion mirrors findings from global studies showing that journalism students often feel more technologically prepared than their educators but less ethically guided.
Curriculum at a crossroads
Rather than advocating for standalone AI courses, the study highlights a growing consensus around curricular convergence embedding AI concepts within existing journalism and communication courses. For journalism schools in the Global South, this approach is both pedagogically sound and practically feasible.
AI intersects with almost every aspect of journalism education. In reporting and research courses, it can support data scraping, trend analysis, and literature reviews. In multimedia storytelling, generative tools can enhance visuals, audio, and video production. In media ethics and journalism studies, AI opens critical discussions around algorithmic bias, automation, surveillance, and the future of newsroom labour.
Educators in the study note that embedding AI into existing courses avoids treating it as a passing trend or a purely technical skill. Instead, it positions AI as part of journalism’s broader intellectual and ethical ecosystem. Several educators already integrate AI-based assignments, such as AI-assisted scripting, translation, or content critique, despite the absence of formal curricular mandates.
Assessment practices are also evolving. Because AI can easily generate essays and answers, traditional evaluation methods are increasingly vulnerable. In response, educators are experimenting with hybrid assessment models, for instance, oral exams, in-class writing, debates, presentations, and tasks that require students to critique or improve AI-generated content. These methods encourage originality while acknowledging AI’s presence rather than pretending it does not exist.
Digital colonialism and the limits of Western AI models
Beyond classroom practices, the study raises deeper structural concerns. Many educators caution that most AI tools are developed within Eurocentric frameworks, trained primarily on Western data, languages, and media norms. When adopted uncritically, these tools risk reinforcing digital colonialism, marginalizing Global South perspectives and misrepresenting local realities.
In South Asia, Journalism operates in environments shaped by political pressure, linguistic diversity, misinformation and fragile democratic institutions. Western AI models often assume stable press freedom, advanced infrastructure, and transparent governance, conditions that do not always apply in the Global South. As a result, AI tools may overlook or distort issues such as human rights violations, political suppression, or local cultural contexts.
The study argues that journalism schools in the Global South should learn from Western models but not replicate them wholesale. Instead, they must co-create contextualized AI pathways that address local challenges like, combating disinformation in native languages, protecting freedom of expression, and amplifying marginalized voices. AI literacy, in this sense, is not just about tools, but about power, representation, and responsibility.
From ethical washing to ethical grounding
Ethics emerges as a central concern throughout the study. While global frameworks such as UNESCO’s AI ethics guidelines and the EU’s AI act offer important direction, educators warn against treating ethics as a static checklist. AI evolves too rapidly for rigid rules to remain relevant.
The research distinguishes between ethical washing, in which institutions promote ethical language without meaningful action, and ethical grounding, in which ethics function as a living, evolving framework embedded in teaching, assessment, and institutional culture. Educators argue that ethical guidelines must be flexible, regularly updated, and grounded in core human values such as fairness, transparency, accountability, and human oversight.
Building responsible AI futures in journalism education
The study concludes that AI can strengthen journalism education in the Global South, but only if integrated thoughtfully. Success depends less on the technology itself and more on institutional leadership, faculty training, ethical clarity, and contextual sensitivity.
Journalism schools must invest in educator upskilling, redesign curricula through convergence, and foster participatory learning environments that promote critical digital literacy. Rather than fearing AI or embracing it uncritically, journalism education must learn to think with AI, questioning its outputs, understanding its limits, and situating it within journalism’s public mission.
While the study focuses on Bangladesh, its insights resonate across South Asia and beyond. As AI continues to evolve, ongoing research and reflective practice will be essential to ensure that journalism education remains not only technologically relevant but also socially responsible, ethically grounded, and deeply human.
We recommend embedding AI into courses, adopting hybrid learning, creating a Global South model, and using ethics as a living guide for meaningful AI integration.
-Samiya Asadi
Reference
Asadi, S., & Sultana, T. Caught in the AI Current: J-School Educators’ Disruption, Adaptation and Future Readiness in the Global South—Insights from Bangladesh. Journalism & Mass Communication Educator, 10776958251407392. https://doi.org/10.1177/10776958251407392
Coauthor
Tania Sultana is an assistant professor in the Department of Journalism and Media Studies at Stamford University, Bangladesh. She co-authored two research books published by the Bangladesh Film Archive in 2016 under separate fellowships. Her research interests include visual culture, cyber-culture, film and gender studies.
