The Social Inevitability of Personal Authenticity in the Age of AI: A Theoretical Analysis of Responsibility-History Structures and the Critical Point of Semantic Corruption

This paper argues that the core impact of rapid AI advancement is not primarily labor substitution or improved content generation, but a structural transformation of society’s decision-making foundation: the separation of meaning from responsibility. Historically, social decisions have required the conjunction of (i) semantic content and (ii) responsibility attribution—i.e., an identifiable fixed point that can irreversibly bear the consequences of judgment. However, generative AI introduces unbounded generativity, near-perfect imitability, and context-stripping capability, enabling discourse to circulate as symbol flows detached from accountable subjects. As a result, society moves toward a critical point of semantic corruption, where responsibility attribution becomes structurally undefined and the probability of decision finalization collapses. To address this, the paper defines personal authenticity not as talent, trust, or brand, but as the social inevitability of an irreversible responsibility history: a condition in which social decision-making cannot be finalized without passing through an attribution fixed point grounded in accumulated, non-retractable commitments. The paper contributes: (i) a formal definition of semantic corruption as responsibility–meaning decoupling, (ii) a four-stage early-signal model of corruption progression (source neutralization → authority dilution → decision paralysis → responsibility vacuum), (iii) necessary and sufficient conditions under which authenticity re-emerges as a social fixed point, and (iv) the role of recording infrastructures—date × numbering schemes, cryptographic hashes/signatures, and DOIs—as coordinate systems that preserve the reference chain of responsibility across time. The central conclusion is that the decisive problem in the AI era is not the generation of information but the reconstruction of irreversible responsibility attribution. AI does not eliminate authenticity; it exposes its structural necessity through semantic corruption dynamics and the re-demand for responsibility fixed points. https://arweave.net/cnd6hqnOQLnkF12e5T8b4OyiRmHucL4_uAPhw4fJ8tA https://arweave.net/GId_D_dSfY1qtqPKhlmEzfi0bA-WC-SLUVPUy4hOcm4