用可操作的测试框架，评估AI是否具备类意识的接口表征。
Artificial Consciousness as Interface Representation
- 基于范畴论构建接口表征模型，将意识视为功能界面而非内在属性。
- 提出S、L、P三类测试，从语言、潜藏、结构三个维度验证类意识行为。
- 适合关注AI意识定义与可验证性研究的学者参考。
人工智能系统是否具有意识是一个充满争议的问题，因其主观体验的定义与可操作性难以实现。本文提出一个框架，将人工意识问题转化为可实证检验的测试。引入三项评估标准——S（主观-语言）、L（潜藏-涌现）、P（现象-结构），统称SLP测试，用于评估人工智能系统是否具备促进类意识属性的接口表征。基于范畴论，我们将接口表征建模为关系基底（RS）与可观测行为之间的映射，类似于特定类型的抽象层。SLP测试共同将主观体验操作化为对关系实体的功能性接口，而非物理系统的内在属性。
原文摘要 · Abstract (English)
Whether artificial intelligence (AI) systems can possess consciousness is a contentious question because of the inherent challenges of defining and operationalizing subjective experience. This paper proposes a framework to reframe the question of artificial consciousness into empirically tractable tests. We introduce three evaluative criteria - S (subjective-linguistic), L (latent-emergent), and P (phenomenological-structural) - collectively termed SLP-tests, which assess whether an AI system instantiates interface representations that facilitate consciousness-like properties. Drawing on category theory, we model interface representations as mappings between relational substrates (RS) and observable behaviors, akin to specific types of abstraction layers. The SLP-tests collectively operationalize subjective experience not as an intrinsic property of physical systems but as a functional interface to a relational entity.
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