Politeness is a core dimension of human communication, yet its role in human-AI information seeking remains underexplored. We investigate how user politeness behaviour shapes conversational outcomes in a cooking-assistance setting. First, we annotated 30 dialogues, identifying four distinct user clusters ranging from Hyperpolite to Hyperefficient. We then scaled up to 18,000 simulated conversations across five politeness profiles (including impolite) and three open-weight models. Results show that politeness is not only cosmetic: it systematically affects response length, informational gain, and efficiency. Engagement-seeking prompts produced up to 90% longer replies and 38% more information nuggets than hyper-efficient prompts, but at markedly lower density. Impolite inputs yielded verbose but less efficient answers, with up to 48% fewer nuggets per watt-hour compared to polite input. These findings highlight politeness as both a fairness and sustainability issue: conversational styles can advantage or disadvantage users, and "polite" requests may carry hidden energy costs. We discuss implications for inclusive and resource-aware design of information agents.

翻译：礼貌性是人类沟通的核心维度，但其在人机信息寻求对话中的作用尚未得到充分探索。本研究以烹饪辅助场景为背景，探究用户礼貌行为如何影响对话结果。首先，我们对30段对话进行标注，识别出从"极度礼貌"到"极度高效"四种不同的用户聚类。随后，我们将研究规模扩展至18,000段模拟对话，涵盖五种礼貌类型（包括不礼貌情形）和三种开放权重模型。结果表明，礼貌性不仅是表面修饰：它会系统性地影响回复长度、信息增益和对话效率。相较于极度高效的请求，寻求互动型的礼貌请求能产生长达90%的回复篇幅和38%的信息增量，但信息密度显著降低。不礼貌的输入则会产生冗长但效率低下的回复，其单位能耗下的信息增量比礼貌输入最多减少48%。这些发现揭示了礼貌性同时涉及公平性与可持续性问题：对话风格可能导致用户处于优势或劣势地位，而"礼貌"请求可能隐含着额外的能源成本。我们进一步探讨了这些发现对包容性及资源感知型信息代理设计的启示。