Computational foundations of the human world

2026-05-02

AI Summary

This study investigates how human societies transform decentralized information into collective judgments and coordinated action under constraints of limited computational resources—specifically time and communication—and reveals the fundamental limitations that computational complexity imposes on social organization. By introducing a novel computational model that transcends traditional Turing-machine paradigms and worst-case complexity assumptions, the work formally characterizes key social mechanisms—such as distributed consensus, hierarchical structures, and external memory—as computational processes for the first time. Integrating tools from distributed computing theory, complexity analysis, and modular modeling, this project establishes a new theoretical direction termed “social computation,” providing a formal framework for analyzing social coordination, scalability, and institutional evolution.

Abstract

Human societies continuously transform scattered information into collective judgments and coordinated action, whether through markets discovering prices, governments allocating resources, communities enforcing norms, or science converging on reliable claims. Importantly, the computational difficulty of collective decision-making, particularly the time and communication required to reach solutions, imposes fundamental constraints on social organization. While theoretical computer science offers formal tools for analyzing such problems, for instance, by analyzing resource requirements, including time and memory, surprisingly, there is no domain of social science that focuses on the nature of computation in the human world. This perspective argues that we now have the opportunity to deploy these computational frameworks to study human social organization, opening research directions at the intersection of computer science and social science. We highlight core social phenomena that can be framed as computational, including (i) distributed consensus and coordinated action, (ii) societal restructuring with scale, (iii) hierarchical and modular structure, and (iv) externalized memory systems. We identify several concepts from theoretical computer science that may provide insight into these phenomena, especially emphasizing more recently developed approaches beyond the paradigm of Turing~Machines and worst-case computational complexity.

Problem

• collective decision-making
• computational complexity
• social organization
• distributed consensus
• theoretical computer science

Innovation

• computational social science
• distributed consensus
• communication complexity
• modular organization
• externalized memory