Reverse Cognitive Pathways: A Vijñaptimātra Account of the Ontological Limits of Artificial Intelligence and its Governance

This paper proposes an inverse trajectory thesis for understanding human-level Artificial Intelligence (AI) by distinguishing computational data processing from authentic information processing. Drawing upon the Vijñaptimātra (consciousness-only) framework, we argue that contemporary AI follows a vijñāna-first developmental path—achieving functional discrimination without lived appropriation (manas) or karmic continuity (citta)—whereas human cognition develops from citta through manas to vijñāna. This ontological asymmetry explains recurrent AI failure modes including specification gaming, simulated empathy, and brittle generalisation. We introduce Prime Knowledge Elements (PKEs) and an Architecture of All Knowledge (AOAK) as computational frameworks for representing authentic information. We propose governance mechanisms integrating Buddhist ethical principles into AI architecture, treating alignment as continuous ethical reflexivity. Testable predictions regarding anthropomorphism gradients, corrigibility dividends, and embodiment limitations are presented. Our analysis concludes that the absence of cetanā (genuine intentionality) represents a fundamental ontological boundary preventing AI from achieving genuine moral agency.

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The authors declare no conflict of interest.

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The datasets used in this study are openly available at [repository link] and the source code is available on GitHub at [GitHub link].

This work did not receive any external funding.