JISARA

Abstract: This paper proposes to develop a model of the factors impacting trust people place in AI Large Language Model (LLM) technology based upon the LLM and related literatures. The trust individuals place in this technology is differentiated from trust placed in organizations or people who develop, sell, deploy and support the AI LLM technologies. The objective is to develop a deeper comprehension of AI LLM users' attitudes and intentions toward that will influence this technology’s adoption and usage. We believe that understanding the human aspect of new AI systems employing Large Language Models (LLMs) like ChatGPT4o and Gemini is important because the LLMs have the capability to influence our everyday work, and the processes used to complete our activities and make decisions. The investigation into a development of a model is important because there is a general awareness that LLMs may present different responses when the same question is re-asked. In addition, LLMs may simply make things up since the technology is simply predicting next-word sequences. However, as seen by the user, these systems and their components produce apparently reasonable or creative outputs that are very highly representative of traditional human-made products. Our questions focus on the factors that may cause users to accept and rely on the LLM systems or ultimately discount or reject their outputs.

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Recommended Citation: Money, W.H., Thanetsunthorn, N., (2025). A Proposed Study of Factors Moderating Degree of Trust in LLM and ChatGPT-like Outputs. Journal of Information Systems Applied Research and Analytics 18(4) pp 67-80. https://doi.org/10.62273/JRRF9742