University of Kwazulu-Natal

Generative Ai And Journalism Hidden Risks Reshaping Information

Bonisiwe Shabane
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generative ai and journalism hidden risks reshaping information

Generative AI tools are reshaping the information environment in ways most audiences never see. From the data that trains them to the labour that maintains them, their inner workings raise urgent questions for journalism and democratic accountability. Our world is in the midst of a disruption triggered by the development of Artificial Intelligence (AI). Companies selling AI tools have become the most valuable corporations in modern times, worth trillions of dollars – more than the GDPs of most countries. They are becoming a pervasive influence on social, commercial, and political life, and shaking up industries. The media industry is among those facing new kinds of challenges due to the rise of AI.

The practice and delivery of journalism, which is a vital component for functioning and healthy democracies, is changing in ways that are not obvious to its consumers. To understand the impact of AI on our information environment and its political consequences requires a basic understanding of what Generative AI is and how it works. We need to “lift the bonnet” on what will increasingly power the information we receive and consume. READ I IT Rules 2025 test balance between safety and rights This research report explores how the growing use of generative AI across society poses risks for journalism as an industry, an institution, a practice and a product; for the wider information commons to which... Qualitative insights from interviews and a survey with a range of experts suggest that GenAI is amplifying many pre-existing long-standing challenges (e.g.

business model and disruption, problematic business practices, information disorder, trust destabilisation). There was a strong appetite for intervention to mitigate such risks (e.g. by demanding greater transparency from AI companies, developing new professional and public literacies, devising new standards and strengthening public policy responses and funding). Photos by Niles Singer/Harvard Staff Photographer The surge of AI produced articles has ignited a series of concerns about the accuracy of news amid the dwindling number of working journalists who serve as a counterforce against the dissemination of inaccurate... Certainly AI does pose ethical and others challenges, but it also offers reporters greater opportunities to do more high-impact, consequential stories, according to Sotiris Sideris, data editor at the Center for Collaborative Investigative Journalism...

14. Data- and generative AI-driven tools allow reporters to analyze in a timelier fashion vast troves of government and business data and identify important patterns that point the way to improvements or uncover questionable, or... “The question today isn’t whether we are using AI in journalism, because we do it already,” but whether “we can do journalism without outsourcing our skepticism, our ethics, and our sense of accountability, both... Artificial intelligence (AI) is transforming sectors from healthcare to education, with its impact on journalism being particularly profound. As the media landscape evolves, AI presents both powerful tools and significant threats to press freedom, integrity, and public trust. On this World Press Freedom Day, we explore how AI is reshaping journalism, examining both the risks it poses and the opportunities it creates.

Journalists today face a growing tide of disinformation and misinformation. As public trust in traditional news media declines, audiences increasingly turn to social media platforms where professional journalism must compete with unverified and often misleading content. AI tools are being used maliciously to generate convincing but false content, including articles, images, audio clips, and deepfake videos. This makes it harder for the public to distinguish fact from fiction. The rapid spread of such content overwhelms newsrooms, which lack the capacity to verify every claim. This challenge, in turn, fuels further distrust in the media.

A striking example occurred in early 2024, when a journalist from France 24 was targeted with a deepfake that manipulated both his voice and article headline. The altered content distorted his reporting on President Emmanuel Macron’s visit to Ukraine, spreading disinformation and undermining his credibility. Such tactics illustrate how even seasoned professionals can fall victim to AI-driven deception. You have full access to this open access article This conceptual article examines the transformative impact of generative artificial intelligence (AI) on journalism through the lens of institutionalism. Building on Stephen D.

Reese’s definition of institutions as “complex social structures” sustained by interlocking norms, roles, technologies, and collective frames of meaning, the article argues that generative AI marks a pivotal shift in journalism’s institutional coherence. Unlike earlier technological disruptions, generative AI directly intervenes in the core creative processes of journalism, challenging traditional norms of authorship, originality, and professional identity. Drawing on scholarship from institutionalism as it pertains to journalism studies and from Human–Machine Communication (HMC), this study situates generative AI as a transformative force within journalism while also acknowledging it as an emerging... We advance theoretical debates regarding the implications of GenAI for journalism and chart a path for future research into the ethical, epistemic, and operational dimensions of AI-driven journalism. Avoid common mistakes on your manuscript. It has long been anticipated, with various degrees of hope, hype, and hysteria, that artificial intelligence (AI) would transform how we live, work, and communicate—and thereby change something fundamental about what it means to...

Such feelings have been on display, as never before, since OpenAI’s signature chatbot, ChatGPT, became an overnight sensation when it was launched in late 2022. What followed during the past several years has been a ceaseless cascade of news coverage and public conversation about AI and its growing influence in people’s everyday lives (e.g., see Yadlin & Marciano, 2024)—from... What triggered this fascination with AI, including utopian and dystopian narratives alike (Lewis et al., 2025), was a crucial advancement in the technology: the wide-scale deployment of generative artificial intelligence (or GenAI), so named... While the actual value of such generative AI outputs has been hotly debated (Arguedas & Simon, 2023; Kieslich et al., 2024; Thomson et al., 2024), with many pointing to their frequent “hallucinations” (or made-up... This is precisely because generative AI, for all its limitations, has comparatively unsurpassed potential to slide into the role of creator/communicator (cf. Guzman & Lewis, 2020; Lewis & Simon, 2023), thus drawing ever closer to what many consider the beating heart of professional work: the creation of original content (e.g., see Coddington, 2014).

Shi, Y.; Sun, L. How Generative AI Is Transforming Journalism: Development, Application and Ethics. Journal. Media 2024, 5, 582-594. https://doi.org/10.3390/journalmedia5020039 Shi Y, Sun L.

How Generative AI Is Transforming Journalism: Development, Application and Ethics. Journalism and Media. 2024; 5(2):582-594. https://doi.org/10.3390/journalmedia5020039 Shi, Yi, and Lin Sun. 2024.

"How Generative AI Is Transforming Journalism: Development, Application and Ethics" Journalism and Media 5, no. 2: 582-594. https://doi.org/10.3390/journalmedia5020039 Shi, Y., & Sun, L. (2024). How Generative AI Is Transforming Journalism: Development, Application and Ethics.

Journalism and Media, 5(2), 582-594. https://doi.org/10.3390/journalmedia5020039 Jones, B. (Co-investigator), Luger, E. (Principal Investigator) & Elsden, C. (Co-investigator)

Research output: Book/Report › Other report N1 - This work has been supported by the PETRAS National Centre of Excellence for IoT Systems Cybersecurity, which has been funded by the UK EPSRC under grant number EP/S035362/1 N2 - This rapid review outlines a range of existing and potential risks generative AI poses if incorporated into journalism, written with newsroom leaders and journalists in mind. It is intended as a quick entry point into live and rapidly evolving discussions of the issues, with links and references out to useful resources – some academic and peer-reviewed, some journalistic. It is not a comprehensive analysis or an exploration of applications or benefits (of which there are a growing number of resources. For ease of navigation, the document is structured into three broad risk categories: editorial, legal, and societal.

The report was created as an output of collaboration between the University of Edinburgh and the BBC R&D Responsible Innovation team, as part of the PETRAS Building Public Value via Intelligible AI project. The work underpinning it includes: a review of existing research and grey literature, expert workshops with BBC staff, interviews and focus groups with BBC journalists. Why have we produced this? Generative AI is a branch of general purpose AI (also referred to as foundation models) that can create media content of varied types, including text, images, audio and code. Generative AI systems such as Large Language Models (LLMs) have pushed the boundaries of what is possible in content generation and created new challenges and risks for society. They will likely have significant impacts on news organisations and journalists as well as audience members/news users, impacting how news is gathered, produced, distributed and consumed.

However, the news media industry currently lacks an advanced understanding of exactly how they work, when and how they fail, and what mitigations are required to ensure they work in the public interest. AB - This rapid review outlines a range of existing and potential risks generative AI poses if incorporated into journalism, written with newsroom leaders and journalists in mind. It is intended as a quick entry point into live and rapidly evolving discussions of the issues, with links and references out to useful resources – some academic and peer-reviewed, some journalistic. It is not a comprehensive analysis or an exploration of applications or benefits (of which there are a growing number of resources. For ease of navigation, the document is structured into three broad risk categories: editorial, legal, and societal. The report was created as an output of collaboration between the University of Edinburgh and the BBC R&D Responsible Innovation team, as part of the PETRAS Building Public Value via Intelligible AI project.

The work underpinning it includes: a review of existing research and grey literature, expert workshops with BBC staff, interviews and focus groups with BBC journalists. Why have we produced this? Generative AI is a branch of general purpose AI (also referred to as foundation models) that can create media content of varied types, including text, images, audio and code. Generative AI systems such as Large Language Models (LLMs) have pushed the boundaries of what is possible in content generation and created new challenges and risks for society. They will likely have significant impacts on news organisations and journalists as well as audience members/news users, impacting how news is gathered, produced, distributed and consumed. However, the news media industry currently lacks an advanced understanding of exactly how they work, when and how they fail, and what mitigations are required to ensure they work in the public interest.

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