CSD as an Organizational Risk Mechanism - Cognitive Species Divergence under AI-Augmented Decision Environments

Abstract As artificial intelligence systems—particularly large language models (LLMs)—are increasingly embedded in organizational decision processes, a new category of risk has emerged that is neither technical nor ethical in the conventional sense. This paper introduces Cognitive Species Divergence (CSD) as an organizational risk mechanism arising from sustained asymmetry between human judgment architectures and AI-generated pseudo-judgment structures. Situated within the Co-Evolutionary Science of Intelligence (CESI), CSD describes a degenerative divergence in which human agents retain formal accountability for decisions while progressively losing their role in judgment formation. Unlike automation risk or model error, CSD operates at the cognitive-architectural level, reshaping how organizations allocate responsibility, form commitments, and interpret uncertainty. Integrating Cognitive Architectonics (CAX) with Irreversibility-First Risk Governance (IFRG) and Lethality-First Fast-Filter Elimination Search (LF²ES), this paper demonstrates that CSD functions as a slow-onset but irreversible organizational failure mode. Once embedded, CSD produces strategic lock-in, accountability displacement, and long-term degradation of institutional judgment capacity. The paper concludes by arguing that CSD cannot be mitigated through better AI alignment or explainability. Instead, it requires negative-first governance controls that prevent AI systems from occupying judgment-forming roles altogether.