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Updated: Sep 20, 2025

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
Using the Nested Structure of Knowledge to Infer What Others Know
Edgar Dubourg1, Thomas Dheilly1, Hugo Mercier1
1Institut Jean Nicod, Département d'Études Cognitives, Ecole Normale Supérieure, Ecole des Hautes Études en Sciences Sociales, Université PSL, Centre National de la Recherche Scientifique (CNRS).
None:
Humans rely on more knowledgeable individuals to acquire information. But when we are ignorant, how are we to tell who is knowledgeable? We propose that human knowledge is nested: People who know only a few things tend to know very common pieces of information, whereas rare pieces of information are known only by people who know many things, including common things. This leads to the possibility of reliably inferring knowledgeability from minimal cues. In this study (N = 848 U.S. adults recruited online), we show that individuals can accurately gauge others' knowledgeability on the basis of very limited information, relying on their ability to estimate the rarity of different pieces of knowledge and on the fact that knowing a rare piece of information indicates a high likelihood of knowing more information in the same theme. Even participants who are largely ignorant of a theme can infer how knowledgeable other individuals are on the basis of the possession of a single piece of knowledge.
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