This study investigates the performance of search engine chatbots powered by large language models in generative political information retrieval. Applying algorithmic accountability as a central theme, this research (a) assesses the alignment of artificial intelligence (AI) chatbot responses with timely political information, (b) investigates the factual correctness and transparency of chatbot-sourced synopses, (c) examines the adherence of chatbots to democratic norms and impartiality ideals, (d) analyzes the sourcing and attribution behaviors of the chatbots, and (e) explores the universality of chatbot gatekeeping across different languages. Using the 2024 Taiwan presidential election as a case study and prompting as a method, the study audits responses from Microsoft Copilot in five languages. The findings reveal significant discrepancies in information readiness, content accuracy, norm adherence, source usage, and attribution behavior across languages. These results underscore the contextual awareness when applying accountability assessment that looks beyond transparency in AI-mediated communication, especially during politically sensitive events.

This study explores how Chinese journalists perceive, use, and report on artificial intelligence (AI) amid the global discourse of AI hype. Drawing on qualitative analysis of 18 in-depth interviews with journalists from a range of Chinese news organisations, this research examines (1) journalists’ algorithmic imaginaries and their role in shaping AI narratives, (2) perceptions of AI hype and strategies for responsible reporting, and (3) the journalistic roles reflected. The findings show that journalists predominantly frame AI as a pragmatic tool for enhancing newsroom efficiency, while also acknowledging its broader societal significance. Although aware of speculative discourses, they reject the label of “media hype,” portraying their coverage as balanced, event-driven, and aligned with public interest. Situated within China’s distinctive political and media environment, this study highlights the complexities of journalistic practice in the algorithmic age and calls for a contextualised theorisation of media hype and AI’s discursive construction in non-Western settings.

 As artificial intelligence (AI) becomes increasingly embedded in journalistic practice, debates often frame it as either a disruptive force or a tool for efficiency. This study moves beyond this dichotomy by examining how journalists themselves interpret, negotiate, and position AI within journalism. Drawing on 19 in-depth interviews with Chinese journalists, and informed by boundary work and boundary object perspectives, the study analyses how AI is selectively integrated, justified, and governed across journalistic processes. The findings show that AI is primarily confined to routine and low-risk tasks, while being excluded from core editorial functions involving judgement, meaning-making, and accountability. The study argues that AI intensifies journalistic boundary work because it challenges journalism not only operationally, but also epistemically and infrastructurally. Journalists therefore engage in layered forms of boundary negotiation that operate across task, discursive, and structural dimensions. At the same time, AI functions as a boundary object mediating relationships among journalists, technology companies, and governance institutions under conditions of asymmetric platform dependency and institutional control.

This dissertation investigates the evolving relationship between journalism and artificial intelligence (AI), focusing on the case of China within a broader global context. Drawing on a critical interpretivist and neo-institutionalist approach, the study explores how AI technologies are transforming journalistic roles, practices, organisational structures, and governance systems. The research conceptualises AI not merely as a set of tools but as a sociotechnical phenomenon that reshapes power relations among key institutional actors—news organisations, technology companies, and the state.

The study employs a multi-method, multi-level research design across five interlinked articles. At the micro level, it examines how Chinese journalists perceive and adapt to AI, and how these perceptions are reflected in their professional role and reporting practices. At the meso level, it analyses the platformisation of news and how algorithmic distribution systems—particularly those developed by major Chinese tech firms—restructure the economic and institutional foundations of journalism. At the macro level, it interrogates the legal and regulatory frameworks governing AI and journalism, comparing developments in China with those in the US and EU to understand cross-national institutional dynamics and normative shifts.

The research highlights a trajectory from institutional adaptability to reinstitutionalisation, showing how the traditional norms of journalism are reconfigured by both market-driven platform logic and state-led political imperatives. The Chinese case, while shaped by its unique media system and historical entanglements, offers insight into broader global tensions between technological innovation, media autonomy, and institutional control. By integrating journalism studies, science and technology studies (STS), political economy, and legal analysis, this dissertation contributes to a transdisciplinary understanding of AI’s impact on the future of journalism.

AI, News, and the State: Reinstitutionalising Journalism in Global China’s Algorithmic Age explores global power shifts and institutional struggles arising from AI’s integration into news production and distribution, with a focus on China and comparative insights from the US and EU. Bridging journalism studies, science and technology studies (STS), political economy, and legal analysis, this dissertation examines how AI is embedded in journalistic practices, media governance, and legal frameworks across divergent political systems. Adopting a critical political economy perspective, the work investigates how AI reconfigures power dynamics between media actors, tech firms, and the state. Focusing on journalism labour, media texts, platformisation, and copyright regimes, it analyses the adaptation of journalists to AI tools and the global race to govern generative technologies. This study provides a multi-level critique of journalism’s reinstitutionalisation under algorithmic conditions, shedding light on its implications for editorial autonomy, democratic values, and public accountability. It provides critical insights for scholars, practitioners, and policymakers seeking to understand the intersections of media, technology, and power in the algorithmic age.

The integration of artificial intelligence (AI) into journalism has become a global phenomenon, with China emerging as a notable player in this evolving landscape. Milestones specific to China, such as the introduction of AI news anchors and the landmark case where AI-generated news articles were granted copyright protection, underscore the country’s pioneering role in this domain. This chapter provides a comprehensive overview of Chinese newsrooms’ employment of AI technologies, including the latest generative AI applications, in newsgathering and the production, presentation, distribution, and consumption of news. It traces historical developments and examines the intricate dynamics among state actors, journalists, tech companies, and the public. By contextualizing AI within China’s unique journalistic culture and regulatory framework, this chapter elucidates the distinct characteristics of AI development in the Chinese media sector. It also highlights the implications of these developments for journalism as an institution, both within China and globally. 

Artificial intelligence has become increasingly pervasive throughout the entire news cycle. In response to this trend, this paper explores journalists’ sociotechnical imaginaries concerning the integration of AI in news production, focusing on their perceptions of AI’s opportunities and ethical challenges. The study also examines the influence of diverse media and discourse cultures on these perceptions by conducting problem-centered interviews with journalists from China, Japan, Switzerland, and the UK. Through an inductive thematic analysis of the interviews, the results reveal that journalists across these four countries acknowledge the potential advantages of AI in journalism, such as enhanced efficiency and improved data analysis. However, their expectations regarding human-machine collaboration in news work vary according to cultural contexts. Furthermore, the findings highlight that the interviewed journalists advocate for the design and implementation of AI systems to adhere to ethical standards.