Locating Evolution in Artificial Successor Systems

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Locating Evolution in Artificial Successor Systems: Intelligent Design Was the Beginning | Zenodo

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Published August 11, 2026

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Locating Evolution in Artificial Successor Systems: Intelligent Design Was the Beginning

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Hedegreen, Dennis1

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Hedegreen Research

Description

Claims that artificial intelligence is &ldquo;evolving&rdquo; often combine evidence drawn from different parts of the same sociotechnical system. This working paper introduces a target-aligned evolutionary audit for artificial successor systems.<br>The method first declares the entity being classified, then tests whether lineage-specific descent, heredity, and differential descendant success are established for that same target. Successor control and persistent environmental feedback are diagnosed separately, while stronger claims about composite evolutionary individuality and species-like separation require additional tests.<br>Comparative cases show why target declaration matters: designed LLM model populations, genome-bearing LLM-agent populations, and LLM-generated program populations can each satisfy Darwinian criteria at different targets while remaining strategically human-controlled.<br>The central claim is narrow: the useful question is not whether AI evolves in the abstract, but which causal relations are established at which target and what additional evidence would justify a stronger classification.

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Keywords

artificial life

artificial evolution

evolutionary individuality

large language models

LLM

levels of selection

model lineage

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10.5281/zenodo.21892666

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Resource type<br>Working paper

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English

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Creative Commons Attribution 4.0 International

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Created

August 11, 2026

Modified

August 11, 2026

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