Impact and integration of AI in public repositories: decolonisation, dissemination and universal Access to scientific knowledge
Keywords:
Research repositories, Artificial intelligence, Scientific knowledge, Scientific decolonization, Dissemination & accessAbstract
Objective: The aim of this study is to analyze the impact and integration of artificial intelligence (AI) in public repositories to promote the democratization and decolonization of scientific knowledge. Methodology: Through a literature review in academic databases: Web of Science (WoS), Scopus, Google Scholar and Dialnet, the applications of AI in content curation, accessibility and visibility of marginalized research were investigated. Results: Findings reveal that AI enhances the capacity of repositories to overcome language barriers, improve interoperability, and highlight research from underrepresented regions. Additionally, the integration of technologies such as machine translation and semantic analysis enables a more equitable and diverse dissemination of scientific knowledge, reducing dependence on traditional metrics and hegemonic editorial structures. Conclusion: The study concludes that AI-supported public repositories are key tools for reducing historical inequalities and fostering more inclusive and representative scientific communication. However, their implementation should follow a critical and equitable model to ensure equal opportunities for researchers worldwide. Contribution: Propose strategies that shift dependence on the current scientific ecosystem toward more inclusive and autonomous models, ensuring the visibility and preservation of scientific knowledge produced by traditionally marginalized communities.
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