人机共生：生成式AI背景下的皮尔斯三元重构

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中图分类号：HO 文献标识码：A 文章编号：1000-0100（2026）01-0025-6

DOI编码：10.16263/j.cnki.23-1071/h.2026.01.006

Human-Machine Symbiosis： A Peircean Triadic Reconstruction in Generative AI

Zhu Shuo-han Chen Yong

（School of Foreign Studies，National University of Defense Technology，Nanjing 21Oooo，China）

This study focuseson the text generationand human-computer interaction processes inthecontextof generative AI.By constructinga“Human-machineDual-cycleInteractionModel”andemployingtheoreticaldeductiontheoreticalanalysis，itexamines thedynamic mechanismsof symboliccognitiongoverned byreciprocaladaptation.Theanalysisdemonstrates：（1）dynamiccognitivereconstructionof symbolsocurs in human-computerinteraction；（2）human-computersymbolconversion exhibits asymmetry；（3）thedynamic textgeneration mechanismof AIsystemsaligns closelywiththecharacteristicsofthe“infinitesemiosis” theory.Furthermore，theuseofgenerativeAIcarriessystemicrisks，including potentiallytrigering“SemanticEntropyIncrease".Acordingly，this study proposes threepathways：establishing anegativeentropymechanismbasedon GANadversarial networks，embedinganethicalframeworkwithinthetriadicinterpretant，anddevelopingadelayedresponsesystem.Ultimately， byadvancing semiotics’paradigmshiftfromamereinterpreterof meaning toaconstructorofsymbioticsubjectivity，thestudy aimstofacilitatethecognitivetransitionfromanthropocentrismtohuman-AIsymbioticsubjectivity.Thesefindingsnotolyextend thecontemporaryrelevanceofPeirce'ssemiotictheorybutalsoprovideamethodological frameworkforadresingthecognitive challenges of symbolic production in the AI era.

KeyWords：AISemiotics；Peircean Triadic Model;Human-machineDual-cycle Interaction Model；GenerativeArtificial Intelligence； Semantic Entropy Increase；symbiotic subjectivity

1引言

2025年1月27日，深度求索正式发布了Deepseek-R1大模型。（剩余10143字）