Reliability and Trust: A Qualitative Study Exploring Perceptions of Gen. AI

Sammanfattning

The use of generative artificial intelligence, such as ChatGPT, has vastly increased in recent years. Through its capability to aid you in nearly any task that can be formulated into a sentence, many people have come to rely on these types of tools in their everyday life, even without fully understanding its underlying mechanisms. This thesis explores how users perceive and interpret ChatGPT outputs, and how these interpretations shape their trust and verification behaviors in this tool. Through six semi structured interviews with ChatGPT users, a thematic analysis identified a plethora of variables affecting trust and verification behaviors. Through analyzing these variables this study found that trust is highly dynamic and context dependent, often being influenced by surface level cues such as output presentation and language rather than factual accuracy. Domain knowledge played a significant role in determining verification ability. These findings highlight user vulnerabilities to misinformation and emphasize the need for improved transparency and user education in AI systems.