Document Type
Thesis
Date of Award
2024
Degree Name
Master of Arts (MA)
Department
Communication Studies
First Advisor
Travis T Loof
Abstract
According to Gallup poll (2023), over the last 50 years there has been a decline in how much Americans trust mass media. While in the 1970’s 72% of the population responded that they trust the media a 'great deal/fair amount', this number dropped to 34% in 2023. Given the decreasing public trust in news, this thesis focused particularly on analyzing trust in the organization, trust in the news story and perceived credibility in AI generative content. In addition to articles created by AI, this study also aimed to analyze how the public perceives information that has been personalized and distributed to users through machine learning. As machine learning is powered by AI and personalized content has become a common practice in the online universe, news outlets are using transparency markers to communicate with their audience about the personalization of news delivered to the user. Therefore, this thesis intended to analyze whether transparency about recommended content affects how individuals perceive news articles. Furthermore, this research also assessed whether an individual's level of acceptance towards AI can influence the credibility and trustworthiness of automated news. Results indicate that AI generated news articles are perceived as less credible compared to human traditional news. These findings have implications for news outlets seeking to adopt AI while trying to maintain and develop trust and credibility in the news. Future research directions and practical recommendations for newsroom practices are discussed.
Subject Categories
Artificial Intelligence and Robotics | Journalism Studies
Keywords
artificial intelligence, credibility, journalism, personalized content, trust
Number of Pages
48
Publisher
University of South Dakota
Recommended Citation
Lobo Paes, Julia, "ARTIFICIAL INTELLIGENCE AND NEWS CONSUMPTION: A STUDY OF TRUST, CREDIBILITY AND TRANSPARENCY IN AUTOMATED JOURNALISM" (2024). Dissertations and Theses. 255.
https://red.library.usd.edu/diss-thesis/255