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April 26, 2026SHILAP Revista de lepidopterologíaOpen Access

Encyclopedic web resources and generative artificial intelligence: a methodological dimension

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Authors

VBValerii Yu. BykovOPOlha P. Pinchuk

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Overview

Article analyzes the impact of generative AI on encyclopedic resources, proposing a framework for quality assurance.

Key Points

  • The research aims to establish a systematic framework for ensuring the epistemic quality of encyclopedic resources integrated with generative AI.
  • Analyzed the impact of generative AI on encyclopedic web resources and user-knowledge interaction.
  • Proposed a framework based on five quality criteria: justification, reliability, accuracy, verifiability, and consistency.
  • Outlined three methodological approaches focusing on human-centered roles, integration scenarios, and multi-level quality control.
  • Identified key risks related to the adoption of generative AI, including degradation of information reliability and cognitive engagement.
  • Emphasized the need for specific quality assurance measures to maintain the epistemic quality of encyclopedic content.
  • Proposed a new framework to guide development and maintenance of encyclopedic resources within generative AI contexts.

Cite This Study

Bykov et al. (2026) studied this question.

synapsesocial.com/papers/69edaa9b4a46254e215b3126https://doi.org/10.55056/cte.990
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