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Article . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
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Confianza ciudadana y aplicación de la IA en la administración pública: un análisis de revisión sistemática

Authors: Hilario Rivas, Jorge Luis; Apaza Mendoza, Jackeline Petronila; Musse Carrasco, Ricardo Santiago; Herrera Torres, Rafael Jesús; Patiño García, Guiceli Codina; Chamoli Falcón, Andy Williams;

Confianza ciudadana y aplicación de la IA en la administración pública: un análisis de revisión sistemática

Abstract

Resumen La introducción de sistemas de inteligencia artificial (IA) en la gestión de registros públicos en América Latina enfrenta desafíos éticos críticos que requieren ser abordados con urgencia. Este problema cobra importancia debido a las repercusiones de la IA en aspectos esenciales como la privacidad, la transparencia y la equidad en el acceso a la información pública. De allí que, el presente artículo tiene como propósito analizar las implicaciones éticas asociadas a la aplicación de la IA en este ámbito, examinando cómo estas problemáticas impactan en la confianza ciudadana y en la eficacia de los sistemas públicos. Para ello, se llevó a cabo una revisión sistemática de la literatura académica sobre el tema planteado, aplicando el método PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). Este enfoque permitió estandarizar las fases de identificación, selección y evaluación crítica de las fuentes consultadas. A partir del análisis de los resultados, se evidenció que las principales inquietudes éticas incluyen: la insuficiencia de regulaciones claras, la presencia de sesgos algorítmicos y la desconfianza tecnológica. Factores que limitan la aceptación de la IA en la administración pública (AP). La principal conclusión de este estudio subraya la necesidad de establecer marcos regulatorios sólidos y mecanismos de supervisión efectivos, asegurando que el uso de la IA sea ético y transparente. Esto no solo fortalecería la legitimidad de estos sistemas, sino que también promovería una gestión pública más justa y responsable.

Abstract The introduction of artificial intelligence (AI) systems in the management of public records in Latin America faces critical ethical challenges that need to be urgently addressed. This issue gains importance due to the repercussions of AI on essential aspects such as privacy, transparency and equity in access to public information. Therefore, the purpose of this article is to analyze the ethical implications associated with the application of AI in this area, examining how these problems impact citizen trust and the effectiveness of public systems. To do so, a systematic review of the academic literature on the topic was carried out, applying the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) method. This approach allowed standardizing the phases of identification, selection and critical evaluation of the sources consulted. Based on the analysis of the results, it was evident that the main ethical concerns include: the lack of clear regulations, the presence of algorithmic biases and technological distrust. Factors limiting the acceptance of AI in public administration (PA). The main conclusion of this study underlines the need to establish solid regulatory frameworks and effective oversight mechanisms, ensuring that the use of AI is ethical and transparent. This would not only strengthen the legitimacy of these systems, but would also promote fairer and more accountable public management.

Keywords

transparency, regulación, ética, transparencia, trust, regulation, sesgos algorítmicos, ethics, algorithmic biases, confianza

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green