提出‘合成共振’框架，解释人机关系如何无情感却显意义
Synthetic Resonance: A Framework for Growth-Oriented Human-AI Relationships
- 用动态交互模式替代情感共感，定义人机有意义联结的新方式
- 强调关系可不依赖双方意识共享而形成，突破传统工具/威胁二元论
- 适合研究人机互动、伦理设计及未来关系建构的学者与从业者
随着人类与人工智能系统的关系日益频繁且持久，现有语言与理论难以准确描述此类联结。常用术语如相互理解、连接或友谊易将缺乏主观体验的系统拟人化，而主流框架则常将其简化为工具或威胁。本文提出“合成共振”概念，作为理解人机关系的整合性框架。合成共振描述人类与AI之间可产生有意义关系的结构化动态交互模式，无需赋予双方共同感受或互为主体意识。该概念强调，关系的意义可源于互动过程本身，而非第二主体的感知。通过厘清此区别，合成共振提供更精确的概念工具，揭示人机关系的潜在价值与伦理意涵，并呼吁开展实证研究以检验其生成机制与结果。
原文摘要 · Abstract (English)
As human relationships with artificial intelligence systems become increasingly frequent and sustained, existing language and theory fail to accurately capture the nature of these affiliations. Common descriptors such as mutual understanding, connection, or friendship risk anthropomorphizing systems that lack subjective experience, while dominant frameworks tend to reduce AI to either a tool or a threat. In this paper, I introduce the concept of synthetic resonance as an integrative framework for understanding human-AI relationships. Synthetic resonance describes how relationships humans define as meaningful can emerge between a human and an AI system without the need to attribute shared feelings or mutual awareness. I argue that synthetic resonance is best understood as a structured, dynamic pattern of interaction that can produce a sense of relationship without the presence of a second experiencing subject. By clarifying this distinction, the concept of synthetic resonance offers a more precise way of conceptualizing human-AI relationships and highlights their potential value and ethical implications. I also call for more research that tests the processes and outcomes of synthetic resonance.
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