The adoption of generative AI technologies is swiftly expanding. Services
employing both linguistic and mul-timodal models are evolving, offering users
increasingly precise responses. Consequently, human reliance on these
technologies is expected to grow rapidly. With the premise that people will be
impacted by the output of AI, we explored approaches to help AI output produce
better results. Initially, we evaluated how contemporary AI services
competitively meet user needs, then examined society's depiction as mirrored by
Large Language Models (LLMs). We did a query experiment, querying about social
conventions in various countries and eliciting a one-word response. We compared
the LLMs' value judgments with public data and suggested an model of
decision-making in value-conflicting scenarios which could be adopted for
future machine value judgments. This paper advocates for a practical approach
to using AI as a tool for investigating other remote worlds. This re-search has
significance in implicitly rejecting the notion of AI making value judgments
and instead arguing a more critical perspective on the environment that defers
judgmental capabilities to individuals. We anticipate this study will empower
anyone, regardless of their capacity, to receive safe and accurate value
judgment-based out-puts effectively.

AI 产出如何产生更好的结果，社会如何将其描绘，以及在冲突价值情境中作出决策模型的研究与应用。