arXiv:2606.12713cs.AI2026-06

为判断AGI是否已实现,提出可操作的定义评估框架。

Definitional alignment before capability alignment: a Design-Science framework for adjudicating claims about AGI

  • 构建双组件框架DAF-AGI,评估AGI定义的合理性
  • 实证检验显示仅性能标准可认证当前系统达AGI
  • 适合政策制定者与技术治理研究者参考

关于人工通用智能(AGI)已实现或仍需数十年的说法,常基于相同证据。'AGI'缺乏统一稳定的指称,不同操作化定义对同一系统可能得出不同结论。本文将其视为设计与治理问题,依据设计科学方法论,提出DAF-AGI框架:包含五项排序标准以评估候选定义的裁决适切性,以及对作者、利益、认证、外部验证和修订权的结构化治理审计。该框架在五个主流测评体系及一个弱化边界立场的文献语料中得到演示,并对一种强主张——当前生成系统因在多项认知任务上超越受教育成年人而构成AGI——进行了压力测试。基于2024–2025年引用来源证据,该主张仅在性能导向的操作化下可被认证;能力本体、心理测量与技能习得路径未予认证,经济类仍不确定,弱化立场拒绝二元裁决。贡献在于概念整合与操作化创新,非实证验证;独立应用、评分者间一致性与外部案例仍需进一步检验。论文进一步提出‘定义主权’作为算法主权的支撑:机构在公众问责下挑战、认证并修订引入技术范畴的能力。

原文摘要 · Abstract (English)

Claims that artificial general intelligence has already arrived and claims that it remains decades away are often defended from overlapping evidence. "AGI" lacks a single shared and stable referent and competing operationalizations can return different verdicts on the same system. This article treats that under-specification as a design and governance problem. Following Design Science Research Methodology, it develops DAF-AGI, a second-order conceptual artifact with two coupled components: five ordinal criteria for assessing the adjudicative fitness of candidate definitions and a structured governance audit of authorship, interest, certification, external verification and revision authority. The artifact is demonstrated on five prominent measurement families and one deflationary boundary position in a documented corpus and then stress-tested against a stylized strong arrival claim: that current generative systems constitute AGI because they outperform a well-educated adult on many cognitive tasks. On evidence from the cited 2024-2025 sources, the claim was certifiable only under a performance-based operationalization; capability-ontology, psychometric and skill-acquisition approaches did not certify it, the economic family remains indeterminate and the deflationary position refuses binary adjudication. The contribution is a novel integration and operationalization, not an empirical validation: independent application, inter-rater testing and author-external cases remain necessary. The paper further proposes definitional sovereignty as an enabling component of algorithmic sovereignty: the institutional capacity to contest, certify and revise imported technological categories under public accountability.

AGI定义治理技术哲学框架设计

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