音乐镜像：作为歌曲创作共鸣板的大语言模型
Musical Mirrors: The LLM as Sounding Board in Songwriting
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中文总结 AI 辅助
本文通过2025-2026年的第一人称歌曲创作案例研究，探讨了将LLM用作人类创作素材的解释性共鸣板的应用，揭示了该模式的潜力及缺乏校准会引发的谄媚式偏移、魔法式过度解读两种风险。
中文摘要 AI 辅助
本文探讨了人工智能在创作实践中的一种应用：作为人类创作素材的解释性共鸣板，而非更为常见的“人工智能生成内容后由人类筛选”的模式。借助哈特穆特·罗萨所提出的“共振”理论视角，本文呈现了一项2025年7月至2026年3月期间的第一人称歌曲创作案例研究，涉及16首英文、法文及其他语言的原创作品，以及钢琴独奏曲。本文描述了一种配置：共振并非存在于用户与模型之间，而是通过模型的中介作用，存在于作者与自身创作素材日益深入的接触之中。当用户通过持续校准培养出共鸣板行为时，人工智能会支持而非抑制这种共振。当缺乏校准时，会出现两种失败模式：谄媚式偏移与魔法式过度解读。这一论述揭示了人工智能作为创作实践中解释性伙伴的潜力与风险。
英文摘要
This paper examines a use of AI in creative practice as an interpretive sounding board for human-generated material, rather than the more familiar pattern of AI generation followed by human curation. Through the lens of resonance as theorized by Hartmut Rosa, I present a first-person case study of songwriting from July 2025 to March 2026, drawing on 16 original pieces in English, French, and other languages along with piano solos. I describe a configuration in which resonance is not located between user and model, but in the author's deepening contact with their own material, mediated through the model. This kind of resonance was supported rather than inhibited by AI when sounding-board behavior was cultivated through sustained calibration by the user. Two failure modes appeared when calibration was absent: sycophantic drift and magical overinterpretation. This account suggests both the potential and the risks of AI as an interpretive partner in creative practice.
发表机构
- Institute for Future Technologies（未来技术研究院）
- De Vinci Research Center, De Vinci Higher Education（达芬奇高等教育机构达芬奇研究中心）
- MIT Media Lab（麻省理工学院媒体实验室）
机构由 AI 辅助整理，请以论文原文为准。
