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Selective divergence between Grokipedia and Wikipedia articles
Saeedeh Mohammadi1,2, Taha Yasseri1,2
1Centre for Sociology of Humans and Machines, Trinity College Dublin and Technological University Dublin, Dublin D02 PN40, Ireland.
Summary
AI encyclopedia Grokipedia offers an alternative to Wikipedia but doesn't uniformly correct biases. It shows topic-specific ideological shifts, favoring narrative over citations, raising concerns about AI knowledge systems.
Area of Science:
- Computational Social Science
- Artificial Intelligence
- Information Science
Background:
- Wikipedia faces criticism for ideological and structural biases.
- AI-generated encyclopedias like Grokipedia aim to provide more objective information.
- The effectiveness of AI in correcting human-generated content biases is not well understood.
Purpose of the Study:
- To computationally compare Grokipedia and Wikipedia content.
- To assess whether AI-driven encyclopedias can systematically reduce biases.
- To analyze differences in content, complexity, and ideological orientation.
Main Methods:
- Large-scale computational comparison of 17,790 matched article pairs.
- Analysis of article length, syntactic complexity, and citation density.
- Measurement of ideological orientation of cited sources, particularly in religion and history topics.
Main Results:
- Grokipedia articles are longer, more complex, and have fewer references per word than Wikipedia articles.
- A bimodal distribution of similarity was observed; many articles matched, but a subset diverged.
- Divergent articles showed a rightward political bias shift in cited sources, especially for religion and history.
Conclusions:
- Grokipedia exhibits selective, topic-specific divergence rather than uniform bias correction.
- AI encyclopedias may prioritize narrative expansion over citation-based verification.
- The study raises questions about transparency, provenance, and governance in AI knowledge systems.
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