Testing a Two-Component Model of Organisational Trust Among Journalists in an AI-Mediated Landscape

The document proposes a study investigating the dynamics of organisational trust among journalists in an era where public relations (PR) content is increasingly created by artificial intelligence. While the journalist-PR relationship is traditionally viewed as an interdependent dyad, industry resource constraints have led reporters to heavily rely on PR materials as operationally reliable epistemic subsidies. The integration of AI into this ecosystem further complicates this dynamic by disrupting traditional audience evaluations of credibility, bias, and authenticity.
To explore this shifting landscape, the research adapts a two-dimensional model of trust originally developed by Hancock et al. (2023) distinguishing between an organisation's functional abilities and its relational characteristics. The central hypothesis is that perceived authenticity will positively moderate the relationship between an organisation’s characteristics and overall trust but will not moderate the relationship between its abilities and trust. Crucially, this moderation is predicted to occur exclusively in human-authored communications, because AI disclosure inherently disrupts traditional evaluations of genuineness and creates a ‘dilemma of AI disclosure.
To test these hypotheses, the study employs a 2 × 2 between-subjects experimental design that manipulates organisation familiarity and content authorship (human-authored vs. AI-generated). The experimental stimulus is a press release from the science and beauty cosmetics industry, an area selected specifically because it requires journalists to evaluate both functional scientific knowledgeability and ethical corporate moral agency. Data collected from a representative sample of journalists via digital slider scales will be analysed using Confirmatory Factor Analysis and moderation modelling to determine exactly how AI-mediated communication alters foundational professional trust.