Evaluating the Impact of AI-Generated News on Public Trust and Information Credibility

Thesis Abstract

The rapid integration of artificial intelligence (AI) technologies within news production processes has fundamentally transformed the landscape of information dissemination, raising critical concerns regarding the authenticity, credibility, and trustworthiness of AI-generated news content. This study investigates the impact of AI-generated news on public trust and the perceived credibility of information, recognizing that while AI can enhance efficiency and reach, it may also propagate misinformation or erode confidence in media sources. The primary aim is to evaluate how exposure to AI-generated news influences audiences' trust levels and their assessment of information credibility, with specific objectives including identifying demographic factors associated with trust variations, assessing the role of source transparency, and exploring the influence of AI-generated content on traditional news credibility metrics. A mixed-method research design was employed, combining quantitative surveys with qualitative focus group discussions. The study population comprised 1,200 adult internet users aged 18–65 across three metropolitan regions, selected via stratified random sampling to ensure demographic representativeness. Quantitative data were collected through structured questionnaires measuring trust, perceived credibility, and familiarity with AI-generated news, with reliability confirmed through Cronbach’s alpha coefficients exceeding 0.80. Qualitative insights were gathered from eight focus groups consisting of 8–10 participants each, exploring perceptions and attitudes towards AI-automated news, with thematic analysis applied to identify recurring themes and sentiments. The quantitative data were analyzed using multiple regression analysis to determine the effects of AI-generated news exposure on trust and credibility perceptions, controlling for variables such as age, education, and media literacy. Thematic analysis facilitated an in-depth understanding of audience attitudes, contextualizing statistical findings. The study hypothesizes that increased exposure to AI-generated news negatively correlates with public trust and perceived credibility, moderated by factors such as source transparency and familiarity with AI. Expected findings suggest that audiences with higher media literacy and awareness of AI processes demonstrate greater trust in AI-augmented news when sources are transparent and content is clearly labeled as AI-generated. Conversely, lack of transparency and unfamiliarity with AI techniques are anticipated to significantly diminish trust and credibility perceptions. The study also posits that demographic variables, including age and education level, influence attitudes towards AI news, with younger and more educated respondents exhibiting comparatively higher trust levels. This research advances understanding in media and communication studies by empirically establishing the relationship between AI-generated news and public trust, contributing to the theoretical discourse on media credibility in the digital age. The findings extend the application of theories such as the Trust Bootstrapping Theory and the Media Dependency Theory by demonstrating how technological transparency and perceived media dependency influence trustworthiness judgments in AI-mediated news environments. The study concludes that while AI has the potential to augment news dissemination, transparency and audience education are crucial in maintaining trust and credibility. It recommends that media organizations adopt clear labeling standards for AI-generated content, enhance digital literacy initiatives, and foster transparency in AI integration practices. The research also advocates for further longitudinal studies to examine evolving perceptions as AI technology advances and becomes more pervasive in the news industry. Overall, the findings provide strategic guidance for media practitioners, policymakers, and technologists committed to preserving the integrity of information in the era of artificial intelligence-driven journalism.