This paper studies how large language models (LLMs) can act as effective,
high-level creative collaborators and ``muses'' for game design. We model the
design of this study after the exercises artists use by looking at amorphous
ink splotches for creative inspiration. Our goal is to determine whether
AI-assistance can improve, hinder, or provide an alternative quality to games
when compared to the creative intents implemented by human designers. The
capabilities of LLMs as game designers are stress tested by placing it at the
forefront of the decision making process. Three prototype games are designed
across 3 different genres: (1) a minimalist base game, (2) a game with features
and game feel elements added by a human game designer, and (3) a game with
features and feel elements directly implemented from prompted outputs of the
LLM, ChatGPT. A user study was conducted and participants were asked to blindly
evaluate the quality and their preference of these games. We discuss both the
development process of communicating creative intent to an AI chatbot and the
synthesized open feedback of the participants. We use this data to determine
both the benefits and shortcomings of AI in a more design-centric role.

这篇论文研究了大型语言模型如何作为高效的、高水平的创作合作者和游戏设计的 “灵感”，并通过艺术家使用模糊的墨斑作为创造灵感的练习为研究设计建模。我们旨在确定与人类设计师实施的创造意图相比辅助人工智能是否能够改善、阻碍或提供另一种质量的游戏。通过将 LLMs 置于决策过程的前沿来测试 LLMs 作为游戏设计者的能力。我们设计了三种不同体裁的原型游戏：（1）极简主义基础游戏，（2）由人类游戏设计师添加特色和游戏感受元素的游戏，（3）直接实施 LLM ChatGPT 的提示输出的特色和感受元素的游戏。我们进行了用户研究，并要求参与者盲目评估这些游戏的质量和偏好。我们讨论了将创造意图传达给 AI 聊天机器人的开发过程和参与者的综合反馈。我们利用这些数据来确定 AI 在更注重设计角色中的优点和不足。