The rapid proliferation of large language models (LLMs) raises critical questions about human creativity and individual expression in an era of AI-assisted creation. When do humans adopt AI suggestions, and what are the implications for individual voice? This study examines these questions through a gamified writing exercise where 74 participants (214 responses) replied to prompts while AI-generated word suggestions were available as they wrote. The game simulates a dystopian future in which an AI is attempting to learn from what remains of human individuality, and disincentivizes AI-like writing. In doing so, it attempts to create conditions that reveal authentic user preferences rather than default behaviors, such as accepting a readily available AI-generated suggestion. Note that this is a deliberate inversion of the "helpful assistant" design pattern; the system is explicitly forbidding you from accepting AI suggestions. We analyze user behavior patterns across different task types, user behaviors, and response characteristics to understand the factors influencing human-AI interaction in creative tasks. The study focuses on when users choose to maintain creative autonomy versus violating the rules of the game and accepting AI assistance. It also explores how these choices relate to response patterns, task characteristics, and user behavior. This gamified approach offers both a framework for studying authentic human-AI interaction and a provocative lens for understanding the tension between efficiency and authenticity in AI-augmented creativity.

翻译：大型语言模型（LLMs）的迅速普及引发了关于AI辅助创作时代人类创造力与个体表达的深刻问题。人类何时会采纳AI建议？这对个人风格有何影响？本研究通过一项 gamified 写作实验探究这些问题：74名参与者（共214份回复）在写作过程中可获得AI生成的词语建议。该游戏模拟了一个反乌托邦的未来场景——AI试图从残存的人类个性中学习，并对类似AI的写作行为施加抑制。通过这种方式，它试图创造能够揭示用户真实偏好的条件，而非默认行为（例如直接接受现成的AI生成建议）。需注意，这刻意颠覆了"乐于助人的助手"设计范式：系统明确禁止用户接受AI建议。我们分析不同任务类型中的用户行为模式、用户行为特征及回复特点，以理解创造性任务中人机交互的影响因素。研究聚焦于用户何时选择维持创作自主权，而非违反游戏规则接受AI协助；同时探讨这些选择与回复模式、任务特征及用户行为之间的关联。这种 gamified 方法既为研究真实人机交互提供了框架，也以富有启发性的视角帮助理解AI增强创造力过程中效率与真实性之间的张力。