Search papers, labs, and topics across Lattice.
This paper presents a theoretical framework for understanding how AI adoption in journalism leads to reconfigurations of editorial authority, focusing on fairness, accountability, and transparency. It identifies two key shifts: an internal migration where editorial judgment is ceded to LLMs within newsrooms, and an external migration where power shifts to platforms and AI vendors. The authors argue that these shifts, if unaddressed, can undermine fairness, accountability, and transparency in journalistic practice, and they critically assess participatory approaches as potential mechanisms for retaining or reclaiming editorial authority.
AI in journalism isn't just automating tasks; it's quietly shifting editorial power away from journalists and towards algorithms and tech companies, threatening the core values of news.
Building on recent interpretivist approaches, we conduct a critical narrative review across journalism studies, human-computer interaction, and FAccT scholarship, conceptualizing editorial authority as the conjunction of decision rights, epistemic warrant, and responsibility. We provide a comprehensive theoretical framework for addressing how concerns on fairness, accountability and transparency emerge, interact, and persist within AI mediated journalistic practice. We identify and describe two concurrent authority reconfigurations driven by AI adoption. First, an internal migration of authority, in which editorial judgment is progressively deferred to large language models (LLMs) embedded within newsroom workflows. This migration occurs not through explicit policy decisions, but through interactional, cognitive, and organizational mechanisms that legitimize AI generated outputs while obscuring responsibility and weakening individual and professional agency. Second, we analyze an external migration of authority, whereby decision making power shifts from news organizations toward platforms, vendors, and infrastructural providers that supply AI systems and distribution channels, exacerbating existing power asymmetries within the media ecosystem. Unaddressed, these reconfigurations risk rendering fairness hard to maintain, accountability difficult to assign and transparency performative. We examine participatory approaches to AI design and deployment in journalism as potential mechanisms for retaining or reclaiming editorial authority. We critically assess both their promise and their structural limitations, highlighting how participation can either meaningfully redistribute authority or function as a tokenistic practice that leaves underlying power relations intact.
