Assessing the Impact of Fake News and AI-Generated Deepfake Videos on Mass Media Credibility: A Comprehensive Analysis

Abstract

This study offers an in-depth analysis of the effects of fake news and AI-generated deepfake videos on the public's perception of the mass media's credibility. The results have made it clear that both types of misinformation are contributing to the declinein trust in traditional media institutions. Credibility is the main driver of fake news, as repeated exposure shapes perception, and cognitive biases can distort it. Deepfake videos, however, pose a more sophisticated challenge, as they use realistic image editing to produce misleading yet genuine content. A valuable contribution of this research is the finding that social media use is one of the factors reinforcing these effects. People who use social media regularly are more likely to be exposed to falseinformation and less likely to verify its truth, leading to increased distrust of the source. Theoretically, the research can contribute to a better understanding of how media consumption patterns can foster trust. It brings together various models to explicate the relationship between misinformation and credibility, offering a panoramic perspective on the problem. In practical terms, the results imply that coordinated action is needed regarding misinformation. There should be collaboration among the use of technology, policy interventions, and educational programs to curb the spread of fake news and restore trust in media systems. To conclude, the paper has highlighted that the issue of misinformation is not limited to technology but should be addressed asa societal issue. Nevertheless, this research has several limitations that must be addressed. The breakneck development of deepfake technology suggests that conclusions may need to be redrawn as new forms emerge. This field should be further investigated in the future using new methodologies and tools.