For centuries, discussions of intelligence have largely been framed within a Cartesian paradigm in which cognition serves as the primary evidence of existence. The proposition “Cogito, ergo sum” (“I think, therefore I am”) established thought as the epistemic foundation of certainty. This paper explores an alternative systemsoriented perspective inspired by the theoretical framework of Self-Preserving Flow (SPF). Rather than treating intelligence as the foundational property of adaptive systems, SPF proposes that long-horizon intelligence presupposes a deeper condition: continuity. The central argument developed here is that a system cannot learn, reason, pursue goals, or adapt across extended temporal horizons unless it preserves sufficient historical continuity to remain identifiable as the same system through time. Identity is therefore interpreted not as a static property, but as a dynamically maintained relationship between present states and historically recoverable lineage. Intelligence emerges not as a primitive phenomenon, but as a higher-order capability built upon persistence, continuity, memory, and identity. The paper develops an ontological and systems-theoretic interpretation of continuity preservation and proposes a conceptual hierarchy: Persistence → Identity → Memory → Learning → Intelligence 1This framework is applied to biological evolution, adaptive systems, artificial intelligence, and long-horizon autonomous agents. The paper further argues that many contemporary discussions of intelligence implicitly commit what may be termed a Time-Scale Fallacy: the assumption that properties observed in shorthorizon optimization systems can be generalized to open-ended adaptive entities operating across extended historical timescales. Finally, the paper explores implications for artificial life and AI alignment, suggesting that the future challenge of advanced intelligent systems may not simply be the production of greater intelligence, but the preservation of historically recoverable identity under conditions of continuous adaptation and entropic pressure.
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Ali Mofradi
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Ali Mofradi (Tue,) studied this question.
synapsesocial.com/papers/6a2117dfd499ed480b170abc — DOI: https://doi.org/10.5281/zenodo.20516898