Algorithmic bottlenecks in evolution: Genetic code, symbolic language, and the Great Filter hypothesis

TL;DR

This paper proposes that the Great Filter in evolution is due to deep algorithmic bottlenecks related to genetic coding and symbolic language emergence, explaining the rarity of advanced civilizations.

Contribution

It introduces a novel perspective that the Great Filter stems from nested information hierarchies and algorithmic thresholds, not just isolated improbable events.

Findings

Identifies coding and language thresholds as key evolutionary bottlenecks.

Uses game theory to analyze stability of signaling and coordination.

Suggests the Great Filter is an intrinsic algorithmic property of evolving systems.

Abstract

The Great Filter hypothesis proposes that the emergence of technological societies capable of interstellar travel depends on a small number of exceptionally hard and highly improbable steps. Traditional versions of this hypothesis enumerate such "hard steps" along the trajectory from inanimate matter to complex technological societies, but diverge in their explanations for why these particular steps should be so improbable. The theory of Major Evolutionary Transitions also faces challenges in identifying which steps should be considered universally "hard" across different evolutionary pathways. In contrast, we argue that two deeply structural obstacles dominate the evolutionary landscape: the coding threshold associated with the origin of the genetic code, and the language threshold associated with the emergence of symbolic communication. We examine the developmental precursors of both transitions and analyze the underlying algorithmic bottlenecks: points at which evolving systems separate code from function, while entangling them within information hierarchies. Using a game-theoretic analysis of coupled signaling and coordination dynamics, we then argue that the corresponding multichannel games exhibit unstable equilibria that render the transitions intrinsically difficult. We conjecture that the so-called Great Filter is best understood not as a sequence of isolated improbable events, but as a nested structure of tangled information hierarchies. Under this interpretation, the rarity of advanced societies follows from the difficulty of crossing these coding thresholds in a competitive noisy environment. This perspective reframes the Great Filter as an algorithmic property of evolving systems, highlighting why only a vanishingly small fraction of life may ever traverse the path toward technological societies capable of interstellar travel.