AI-Augmented Science and the New Institutional Scarcities

2026-05-04

AI Summary

This study addresses how the widespread deployment of artificial intelligence undermines the institutional monopoly of scientific organizations over legitimacy judgments, thereby generating a new form of institutional scarcity. Integrating insights from institutional economics and sociotechnical systems theory, the paper analyzes the mechanisms through which AI reconfigures epistemic labor in science and identifies verification signals, legitimacy, verifiable provenance, and cognitive integration capacity as the emergent scarce elements underpinning scientific certification in the AI era. Among these, cognitive integration capacity constitutes a core bottleneck resistant to technological substitution. The research demonstrates that AI cannot autonomously resolve the scientific community’s bounded tolerance for delegated cognition and argues that enhancing science through AI hinges not on tool optimization but on deliberate institutional redesign.

Abstract

Competent-looking judgment, including selecting, ranking, attributing, and certifying, is now produced at scale at marginal cost approaching zero, inverting the dominant economics-of-AI reading that treats judgment as the scarce complement to cheap prediction. Scientific institutions, distinctively, manufacture legitimate judgment, so they do not merely adapt to AI; they compete with it for the same functional role. Four complements then become scarce and load-bearing for AI-augmented science: verified signal, legitimacy, authentic provenance, and integration capacity (the community's tolerance for delegated cognition). Of these four, integration capacity is the least developed for scientific institutions and the most binding: no improvement in AI tooling can buy it. The frontier for AI-augmented science is not acceleration; it is the redesign of the certifying infrastructure around these new scarcities.

Problem

• AI-augmented science
• institutional scarcities
• legitimate judgment
• integration capacity
• certifying infrastructure

Innovation

• AI-augmented science
• institutional scarcity
• legitimate judgment
• integration capacity
• certifying infrastructure