The Simplicity Paradox: Why Evolution Does Not Produce Universally Complex Agents

2026-06-17

AI Summary

This study addresses why human societies have not evolved universally high-complexity individuals and instead rely extensively on simplified heuristics. It proposes a theory of cognitive economy, arguing that information acquisition, processing, and coordination entail non-negligible costs, leading natural selection in complex environments to favor heterogeneous populations: most individuals employ low-cost heuristics, while a minority of specialists undertake complex decision-making, thereby establishing cognitive division of labor. This framework treats simplicity as a prerequisite for scalable social organization and offers a unified explanation for bounded rationality, rational inattention, hierarchical structures, market mechanisms, and cultural evolution. It further shows how specialist decision-makers secure disproportionate rents and status to circumvent the volunteer’s dilemma. Theoretical modeling demonstrates that societies with cognitive division of labor achieve greater adaptive fitness when the cost savings from distributed simplification outweigh the utility losses from reduced autonomy and imperfect delegation.

Abstract

It has been well established that information improves decisions, pushing the population forward as more information becomes available. Nevertheless, a wide range of empirical evidence shows that humans avoid complexity, delegate judgement, and prefer simplified social worlds. This tension raises an evolutionary puzzle: if knowledge is economically valuable and therefore evolutionarily beneficial, why do populations not converge towards universally informed and complex agents? In this study, we propose a theory of cognitive economy in which information has positive utility but costly acquisition, processing, and coordination. In complex environments, selection can favour heterogeneous populations: most individuals use low-cost heuristics and simplified choice architectures, whereas a minority of agents or institutions specialize in information processing. This cognitive division of labour reduces decision costs while preserving much of the value created by knowledge. We formalize this trade-off by comparing societies of uniformly complex agents with societies containing simpler agents and a specialized decision-making centre. The latter can dominate when the costs saved by distributed simplicity exceed the utility lost through reduced individual autonomy and imperfect delegation. Crucially, the specialized decision-maker need not face a volunteer's dilemma, because its private payoff can exceed that available under universal complexity through rents, status, control or superior information. The framework links bounded rationality, rational inattention, hierarchy, markets, and cultural evolution, and suggests that simplicity is not a failure of adaptation but a precondition for scalable social organization.

Problem

• evolutionary puzzle
• cognitive complexity
• information processing
• bounded rationality
• simplicity

Innovation

• cognitive economy
• division of labour
• bounded rationality
• rational inattention
• evolutionary game theory