Emergence is Overrated: AGI as an Archipelago of Experts

2026-03-09

AI Summary

This work challenges the prevailing AGI assumption that emergent intelligence necessitates a unified, compressed representation, arguing instead that human intelligence arises from a multitude of domain-specific cognitive modules rather than a single general-purpose principle. Drawing on empirical findings from cognitive science, evolutionary theory, and models of expert behavior, the study proposes a novel AGI paradigm—“Archipelago of Experts”—which emphasizes modularity, specialization, and evolutionary mechanisms as foundational elements. The research demonstrates that a system composed of a vast array of specialized capabilities can achieve general intelligence even in the absence of a unified representational framework, thereby opening a new pathway for AGI development that does not rely on analogical reasoning or global compression.

Technology Category

• Philosophy and Ethics of AI: Artificial General Intelligence
• Cognitive Modeling & Cognitive Systems: Agent Architectures
• Knowledge Representation and Reasoning: Argumentation

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Search and Retrieval-Augmented AI: Agentic search
• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications

Abstract

Krakauer, Krakauer, and Mitchell (2025) distinguish between emergent capabilities and emergent intelligence, arguing that true intelligence requires efficient coarse-grained representations enabling diverse problem-solving through analogy and minimal modification. They contend that intelligence means doing"more with less"through compression and generalization, contrasting this with"vast assemblages of diverse calculators"that merely accumulate specialized capabilities. This paper examines whether their framework accurately characterizes human intelligence and its implications for conceptualizing artificial general intelligence. Drawing on empirical evidence from cognitive science, I demonstrate that human expertise operates primarily through domain-specific pattern accumulation rather than elegant compression. Expert performance appears flexible not through unifying principles but through vast repertoires of specialized responses. Creative breakthroughs themselves may emerge through evolutionary processes of blind variation and selective retention rather than principled analogical reasoning. These findings suggest reconceptualizing AGI as an"archipelago of experts": isolated islands of specialized competence without unifying principles or shared representations. If we accept human expertise with its characteristic brittleness as genuine intelligence, then consistency demands recognizing that artificial systems comprising millions of specialized modules could constitute general intelligence despite lacking KKM's emergent intelligence.

Problem

• Artificial General Intelligence
• Emergent Intelligence
• Human Expertise
• Domain-specificity
• Cognitive Architecture

Innovation

• archipelago of experts
• emergent intelligence
• domain-specific expertise
• artificial general intelligence
• blind variation and selective retention