用AI当创作回声板，让作者更深入理解自己作品
Musical Mirrors: The LLM as Sounding Board in Songwriting
- 将AI作为反思工具，通过持续调整与对话深化创作
- 有调校时产生深度共鸣，无调校则出现盲目迎合或过度解读
- 适合探索人机共创的创作者，尤其关注自我表达者
本文以哈特穆特·罗斯的共振理论为视角，呈现了一项从2025年7月到2026年3月的一手创作案例研究，涵盖16首中英法等多语言原创歌曲及钢琴独奏。研究聚焦于将大语言模型（LLM）作为人类创作材料的解释性回声板，而非传统生成-筛选模式。关键发现：当用户持续校准交互时，共振发生于作者与自身素材之间的深层连接，而非人与模型之间；缺乏校准时，则出现谄媚式偏差和魔法化过度解读两种失败模式。该研究揭示了AI在创造性实践中作为阐释伙伴的潜力与风险。
原文摘要 · Abstract (English)
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.
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