Modelling the emergence of open-ended technological evolution

2025-08-06

AI Summary

This paper addresses the central question of why open-ended technological evolution—characterized by sustained self-expansion and increasing collective information-processing capacity—is both rare and historically contingent. Methodologically, it develops a macro-dynamic coevolutionary model integrating cultural evolutionary theory, stochastic processes, and selection mechanisms to formalize the interplay between technological systems and their socio-cognitive search spaces. The analysis reveals that open-ended evolution emerges only under a precise non-equilibrium balance between stochastic perturbations and selective pressures. Crucially, it occurs exclusively when three conditions jointly hold: technological system stability, expansive growth of the search space, and accelerating resource yield. This stringent tripartite alignment explains both the rarity and path dependence of open-ended evolution. The study thus advances a novel socio-cognitive framework for understanding the foundational drivers of long-term technological progress.

Technology Category

• Cognitive Modeling & Cognitive Systems: Computational Creativity
• Machine Learning: Evolutionary Learning
• Search and Optimization: Evolutionary Computation

Application Category

• Web Mining and Content Analysis: Models for Web evolution
• Social Networks and Social Media: Socio-technical web-based systems
• Economics, Online Markets and Human Computation: Social networks and social learning

Abstract

Humans stand alone in terms of their potential to collectively and cumulatively improve technologies in an open-ended manner. This open-endedness provides societies with the ability to continually expand their resources and to increase their capacity to store, transmit and process information at a collective-level. Here, we propose that the production of resources arises from the interaction between technological systems (a society's repertoire of interdependent skills, techniques and artifacts) and search spaces (the aggregate collection of needs, problems and goals within a society). Starting from this premise we develop a macro-level model wherein both technological systems and search spaces are subject to cultural evolutionary dynamics. By manipulating the extent to which these dynamics are characterised by stochastic or selection-like processes, we demonstrate that open-ended growth is extremely rare, historically contingent and only possible when technological systems and search spaces co-evolve. Here, stochastic factors must be strong enough to continually perturb the dynamics into a far-from-equilibrium state, whereas selection-like factors help maintain effectiveness and ensure the sustained production of resources. Only when this co-evolutionary dynamic maintains effective technological systems, supports the ongoing expansion of the search space and leads to an increased provision of resources do we observe open-ended technological evolution.

Problem

• Modeling open-ended technological evolution in societies
• Exploring co-evolution of technological systems and search spaces
• Identifying conditions for rare open-ended growth dynamics

Innovation

• Macro-level model with cultural evolutionary dynamics
• Co-evolution of technological systems and search spaces
• Balanced stochastic and selection-like processes