Skip to content
aiqbench takeAI & Society

aiqbench analysis

The study compares 1,000 matched Wikipedia and Grokipedia articles and finds that the AI-generated encyclopedia cites less academic and journalistic material and more user-generated content and NGO or think-tank sources. The authors call this "epistemic substitution," which is a useful framing for anyone thinking about provenance in generative systems. The evidence is observational and limited to citation patterns, so it shows where claims are sourced differently, not whether those sources are more or less accurate.
Source coveringarXiv

Epistemic Substitution: How Grokipedia's AI-Generated Encyclopedia Restructures Authority

arXiv2 min read

arXiv:2512.03337v2 Announce Type: replace-cross Abstract: For more than two decades, Wikipedia has represented a decentralized, human-curated model of encyclopedic knowledge production. The emergence of AI-generated encyclopedias, such as Grokipedia, raises a fundamental question: do human- and AI-curated knowledge systems rely on the same foundations of epistemic authority? We examine this question through a comparative analysis of 1,000 matched Wikipedia--Grokipedia article pairs, comprising nearly 600,000 citation instances. Using an eight-category classification scheme, we construct the epistemic profiles of articles to examine the institutional composition of their cited sources. Our findings reveal substantial differences in sourcing practices. Grokipedia relies proportionally less on academic and journalistic sources and more on user-generated content and NGO and think-tank publications. These differences persist across broad topic domains, although their magnitude varies by subject. We also find that Grokipedia adds citations approximately linearly as articles grow, whereas Wikipedia exhibits greater variation in citation density. Together, these findings suggest a shift in the institutional sources invoked to justify encyclopedic claims, which we characterize as epistemic substitution. For the same topics, the two encyclopedias rest on different institutional sources. Our findings underscore the importance of systematic, ongoing audits of information provenance for accountability in generative knowledge systems.

Abstract:For more than two decades, Wikipedia has represented a decentralized, human-curated model of encyclopedic knowledge production. The emergence of AI-generated encyclopedias, such as Grokipedia, raises a fundamental question: do human- and AI-curated knowledge systems rely on the same foundations of epistemic authority? We examine this question through a comparative analysis of 1,000 matched Wikipedia--Grokipedia article pairs, comprising nearly 600,000 citation instances. Using an eight-category classification scheme, we construct the epistemic profiles of articles to examine the institutional composition of their cited sources. Our findings reveal substantial differences in sourcing practices. Grokipedia relies proportionally less on academic and journalistic sources and more on user-generated content and NGO and think-tank publications. These differences persist across broad topic domains, although their magnitude varies by subject. We also find that Grokipedia adds citations approximately linearly as articles grow, whereas Wikipedia exhibits greater variation in citation density. Together, these findings suggest a shift in the institutional sources invoked to justify encyclopedic claims, which we characterize as epistemic substitution. For the same topics, the two encyclopedias rest on different institutional sources. Our findings underscore the importance of systematic, ongoing audits of information provenance for accountability in generative knowledge systems.

Social and Information Networks (cs.SI); Computation and Language (cs.CL); Computers and Society (cs.CY); Digital Libraries (cs.DL)

K.4.2; H.3.5; I.2.7

arXiv:2512.03337 [cs.SI]

(or arXiv:2512.03337v2 [cs.SI] for this version)

https://doi.org/10.48550/arXiv.2512.03337 Focus to learn more arXiv-issued DOI via DataCite

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Full text under the publisher's open licence · 301 words

Related coverage