Encyclopedic web resources and generative artificial intelligence: a methodological dimension

This article addresses a critical gap in the methodological foundations for designing, operating, and developing encyclopedic web resources in the context of generative artificial intelligence (GenAI) integration. While existing research has examined GenAI's applications in information systems, a systematic framework for preserving epistemic quality in encyclopedic knowledge systems remains underdeveloped. We analyze the transformational impact of GenAI on the structure, functionality, and content of encyclopedic web resources as components of web-oriented automated information systems. We argue that GenAI functions not merely as an automation tool but as a factor fundamentally altering user-knowledge interaction patterns, necessitating reconceptualization of encyclopedic resources as human-machine intelligent systems. The article examines the principal methodological risks of GenAI adoption, with particular emphasis on information reliability degradation and cognitive engagement reduction in knowledge creation processes. These risks, we contend, directly affect the epistemic quality of encyclopedic content and demand specific quality assurance mechanisms. We propose a framework for ensuring epistemic quality structured around five criteria: justification, reliability, accuracy, verifiability, and consistency. Three complementary methodological approaches are outlined: a human-centered approach delineating roles between GenAI and experts; a hybrid approach defining GenAI integration scenarios; and a multi-level quality control approach emphasizing preventive mechanisms. We highlight the limitations of traditional post hoc peer review under conditions of widespread GenAI adoption. The proposed framework, we suggest, provides methodological foundations for developing encyclopedic web resources while maintaining their scientific and educational value. However, we acknowledge that this conceptual framework requires empirical validation through implementation in specific encyclopedic platforms.