When the Commons Appropriates a Large Language Model: How WikiVault Reshaped Korean Wikipedia

2026-10-05

AI Summary

This study addresses the challenge of large language models (LLMs) disrupting the knowledge commons, examining how communities can balance content production with quality assurance while proactively adapting to LLM tools. To investigate this, we propose a novel paradigm of community “appropriation” of LLMs, utilizing the Korean Wikipedia platform WikiVault as a case study through a mixed-methods approach comprising in-depth interviews, platform-scale analysis, and a matched quasi-experiment. Our findings reveal that LLM integration significantly amplifies core editors’ productivity and restructures their workflows, while simultaneously introducing evaluative logics derived from English Wikipedia. This research elucidates how emerging technologies reshape collaborative ecosystems and facilitate adaptive governance, offering a new theoretical framework and empirical evidence for community-driven knowledge production in the era of large language models.

Abstract

Large Language Models (LLMs) have disrupted the balance between content production and quality assurance that sustains knowledge commons, leading many to prohibit or restrict their use. But what happens when a community instead appropriates an LLM-powered tool for its own needs? We investigate this question through WikiVault, an LLM-powered editing tool developed within the Korean Wikipedia community and used primarily for translation. Combining ten interviews, platform-scale analyses, and matched quasi-experimental comparisons, we examine how WikiVault reshaped knowledge production on Korean Wikipedia. We find the tool 1) drastically amplified the production capacity of a small group of experienced editors, producing longer and more widely viewed articles; 2) shifted work toward reviewing articles and importing content; 3) imported not only content but also editorial judgments from English Wikipedia. Our findings show how LLM adoption can rebalance the interdependent work that sustains knowledge commons, while illustrating how communities can learn from emerging technologies through use and adapt their governance accordingly.

Problem

• Large Language Models
• Knowledge Commons
• Wikipedia
• Content Production
• Community Governance

Innovation

• Large Language Models
• Knowledge Commons
• WikiVault
• Quasi-experimental Design
• Community Governance