Inteligencia artificial y función administrativa en América Latina: riesgos jurídico-administrativos y lineamientos para prevenir la reproducción de desigualdades

dc.contributor.advisorCárdenas Sierra, Robinson Ari
dc.contributor.authorHernández Granados, Diana Shamara
dc.contributor.corporatenameUniversidad Santo Tomás
dc.contributor.cvlachttps://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001218158
dc.contributor.googlescholarhttps://scholar.google.com/citations?user=4IMyBP0AAAAJ&hl=es
dc.contributor.orcidhttps://orcid.org/0000-0002-4773-0233
dc.date.accessioned2026-08-06T14:20:10Z
dc.date.available2026-08-06T14:20:10Z
dc.date.issued2026-08-05
dc.descriptionEl artículo analiza la implementación de los sistemas de inteligencia artificial en la función administrativa latinoamericana desde un enfoque de derechos humanos, con el propósito de formular lineamientos jurídico-administrativos orientados a prevenir la reproducción de desigualdades. La investigación se desarrolla mediante una metodología cualitativa, documental, comparada y hermenéutico-jurídica, centrada en normas, políticas públicas, estándares internacionales y doctrina reciente sobre inteligencia artificial, administración pública y derechos fundamentales. El análisis sostiene que la IA puede apoyar tareas de clasificación, priorización, predicción y recomendación, pero no sustituir la formación jurídica de la voluntad administrativa ni la motivación del acto. A su vez, los resultados muestran que la opacidad algorítmica, el sesgo, la discriminación indirecta, la afectación del contradictorio, la delegación encubierta y los problemas probatorios comprometen la igualdad material, el debido proceso, el control judicial y la responsabilidad estatal. Finalmente, se proponen los lineamientos basados en la delimitación previa del uso, clasificación de riesgos, gobernanza de datos, transparencia, auditoría, evaluación de impacto, motivación reforzada y reserva de decisión humana.
dc.description.abstractThe article analyzes the implementation of artificial intelligence systems in the Latin American administrative function from a human rights approach, with the purpose of formulating legal- administrative guidelines aimed at preventing the reproduction of inequalities. The research is developed through a qualitative, documentary, comparative, and legal-hermeneutic methodology, focused on legal norms, public policies, international standards, and recent scholarship on artificial intelligence, public administration, and fundamental rights. The analysis argues that AI may support classification, prioritization, prediction, and recommendation tasks, but it cannot replace the legal formation of administrative will or the statement of reasons for administrative acts. In turn, the findings show that algorithmic opacity, bias, indirect discrimination, impairment of adversarial participation, hidden delegation, and evidentiary problems compromise substantive equality, due process, judicial review, and state liability. Finally, the article proposes guidelines based on prior delimitation of use, risk classification, data governance, transparency, auditing, impact assessment, reinforced reasoning, and human decision-making reservation.
dc.description.degreelevelMaestríaspa
dc.description.degreenameMaestría en Derecho Administrativospa
dc.description.domainhttp://www.ustatunja.edu.co/investigacion
dc.format.mimetypeapplication/pdf
dc.identifier.citationHernández Granados, D. S. (2026). Inteligencia artificial y función administrativa en América Latina: riesgos jurídico-administrativos y lineamientos para prevenir la reproducción de desigualdades. [Trabajo de Maestría, Universidad Santo Tomás].Repositorio Instituticional
dc.identifier.instnameinstname:Universidad Santo Tomásspa
dc.identifier.reponamereponame:Repositorio Institucional Universidad Santo Tomásspa
dc.identifier.repourlrepourl:https://repository.usta.edu.cospa
dc.identifier.urihttp://hdl.handle.net/11634/73825
dc.language.isospa
dc.publisherUniversidad Santo Tomásspa
dc.publisher.branchCRAI-USTA Tunja
dc.publisher.facultyFacultad de Derechospa
dc.publisher.programFacultad de Derechospa
dc.relation.referencesAgencia Española de Protección de Datos. (2021). Requisitos para auditorías de tratamientos que incluyan IA. https://www.aepd.es/documento/requisitos-auditorias-tratamientos-incluyan- ia.pdf
dc.relation.referencesAhn, M. J., y Chen, Y. C. (2022). Digital transformation toward AI-augmented public administration: The perception of government employees and the willingness to use AI in government. Government Information Quarterly, 39(2), 101664. https://doi.org/10.1016/j.giq.2021.101664
dc.relation.referencesAlon, S., y Busuioc, M. (2021). Human-AI interactions in public sector decision-making: “Automation bias” and “selective adherence” to algorithmic advice. arXiv. https://doi.org/10.48550/arXiv.2103.02381
dc.relation.referencesBanco Mundial. (2021). Informe sobre el desarrollo mundial 2021: Datos para una vida mejor. World Bank. https://www.worldbank.org/en/publication/wdr2021
dc.relation.referencesCobbe, J., Lee, M. S. A., y Singh, J. (2021). Reviewable automated decision-making: A framework for accountable algorithmic systems. Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency. https://doi.org/10.48550/arXiv.2102.04201
dc.relation.referencesComisión Económica para América Latina y el Caribe [CEPAL]. (2025). Índice Latinoamericano de Inteligencia Artificial (ILIA) 2025. https://hdl.handle.net/11362/82514
dc.relation.referencesComisión Europea. (2026). AI Act. Shaping Europe’s Digital Future. https://digital- strategy.ec.europa.eu/en/policies/regulatory-framework-ai
dc.relation.referencesConsejo de Estado. (2021). Radicado 25000-23-41-000-2020-00573-01. https://consejodeestado.gov.co/documentos/boletines/242/25000-23-41-000-2020-00573- 01.pdf
dc.relation.referencesCorte Constitucional de Colombia. (2021). Sentencia C-162 de 2021. https://www.funcionpublica.gov.co/eva/gestornormativo/norma.php?i=173213
dc.relation.referencesCovilla, J. C., Hofmann, H. C. H., y Pflücke, F. (2025). Artificial intelligence and administrative discretion: Exploring adaptations and boundaries. European Journal of Risk Regulation, 16, 36–50. https://doi.org/10.1017/err.2024.76
dc.relation.referencesCruz, A., Mora, R., Andonova, V., Rosales Torres, C. S., Carrasco, C., y Castillo Leska, A. (2025). fAIr Tech Radar: Exploring the adoption of artificial intelligence in Latin America and the Caribbean. Inter-American Development Bank. https://doi.org/10.18235/0013837
dc.relation.referencesde Bruijn, H., Warnier, M., y Janssen, M. (2022). The perils and pitfalls of explainable AI: Strategies for explaining algorithmic decision-making. Government Information Quarterly, 39(2), 101666. https://doi.org/10.1016/j.giq.2021.101666
dc.relation.referencesDepartment for Science, Innovation and Technology. (2023). A pro-innovation approach to AI regulation. GOV.UK. https://www.gov.uk/government/publications/ai-regulation-a-pro- innovation-approach/white-paper
dc.relation.referencesDepartamento Nacional de Planeación [DNP]. (2025). Política Nacional de Inteligencia Artificial: Documento CONPES 4144. https://colaboracion.dnp.gov.co/CDT/Conpes/Econ%C3%B3micos/4144.pdf
dc.relation.referencesDíaz, N., Del Ser, J., Coeckelbergh, M., López, M., Herrera, E., y Herrera, F. (2023). Connecting the dots in trustworthy artificial intelligence: From AI principles, ethics, and key requirements to responsible AI systems and regulation. Information Fusion, 99, 101896. https://doi.org/10.1016/j.inffus.2023.101896
dc.relation.referencesEuropean Data Protection Board y European Data Protection Supervisor. (2021). Joint Opinion 5/2021 on the proposal for a Regulation laying down harmonised rules on artificial intelligence. https://www.edpb.europa.eu/our-work-tools/our-documents/edpbedps-joint- opinion/edpb-edps-joint-opinion-52021-proposal_en
dc.relation.referencesGerards, J., y Zuiderveen, F. (2025). Protected grounds and the system of non-discrimination law in the context of algorithmic decision-making and artificial intelligence. arXiv. https://doi.org/10.48550/arXiv.2509.08837
dc.relation.referencesGreen, B. (2022). The flaws of policies requiring human oversight of government algorithms. Computer Law y Security Review, 45, 105681. https://doi.org/10.1016/j.clsr.2022.105681
dc.relation.referencesHarper, S. B., y Weber, E. S. (2023). Fiduciary responsibility: Facilitating public trust in automated decision making. arXiv. https://doi.org/10.48550/arXiv.2301.10001
dc.relation.referencesInformation Commissioner’s Office. (2025). Artificial intelligence. https://ico.org.uk/for- organisations/uk-gdpr-guidance-and-resources/artificial-intelligence/
dc.relation.referencesKaminski, M. E., y Malgieri, G. (2021). Algorithmic impact assessments under the GDPR: Producing multi-layered explanations. International Data Privacy Law, 11(2), 125–144. https://doi.org/10.1093/idpl/ipaa020
dc.relation.referencesLanger, C. (2024). Decision-making power and responsibility in an automated administration. Discover Artificial Intelligence, 4, 59. https://doi.org/10.1007/s44163-024-00152-1
dc.relation.referencesLevy, E. (2025). An enabling regulatory framework for artificial intelligence in Latin America and the Caribbean (IDB Technical Note No. 3241). Inter-American Development Bank. https://publications.iadb.org/publications/english/document/An-Enabling-Regulatory- Framework-for-Artificial-Intelligence-in-Latin-America-and-the-Caribbean.pdf
dc.relation.referencesLevy, K., Chasalow, K., y Riley, S. (2021). Algorithms and decision-making in the public sector. https://doi.org/10.48550/arXiv.2106.03673
dc.relation.referencesLoi, M., y Spielkamp, M. (2021). Towards accountability in the use of artificial intelligence for public administrations. Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society, 757–766. https://doi.org/10.1145/3461702.3462631
dc.relation.referencesLyons, H., Velloso, E., y Miller, T. (2021). Designing for contestation: Insights from administrative law. arXiv. https://doi.org/10.48550/arXiv.2102.04559
dc.relation.referencesMantelero, A., y Esposito, M. S. (2024). An evidence-based methodology for human rights impact assessment (HRIA) in the development of AI data-intensive systems. https://doi.org/10.48550/arXiv.2407.20951
dc.relation.referencesMetcalf, J., Moss, E., Singh, R., Tafese, E., y Watkins, E. A. (2022). A relationship and not a thing: A relational approach to algorithmic accountability and assessment documentation. https://doi.org/10.48550/arXiv.2203.01455
dc.relation.referencesMinistério da Ciência, Tecnologia e Inovação. (2024). Plano Brasileiro de Inteligência Artificial 2024-2028: IA para o bem de todos. Governo Federal do Brasil. https://www.gov.br/mcti/pt-br/acompanhe-o-mcti/noticias/2024/07/plano-brasileiro-de- inteligencia-artificial-preve-r-23-bilhoes-em-investimentos-em-quatro-anos
dc.relation.referencesMinisterio de Ciencia, Tecnología, Conocimiento e Innovación. (2024). Política Nacional de Inteligencia Artificial. Gobierno de Chile. https://www.minciencia.gob.cl/areas/inteligencia-artificial/politica-nacional-de- inteligencia-artificial/
dc.relation.referencesMokander, J., Morley, J., Taddeo, M., y Floridi, L. (2021). Ethics-based auditing of automated decision-making systems: Nature, scope, and limitations. Science and Engineering Ethics, 27, Article 44. https://doi.org/10.1007/s11948-021-00319-4
dc.relation.referencesNational Institute of Standards and Technology [NIST]. (2023). Artificial Intelligence Risk Management Framework (AI RMF 1.0). U.S. Department of Commerce. https://doi.org/10.6028/NIST.AI.100-1
dc.relation.referencesOECD.AI. (2026). OECD AI Principles overview. Organisation for Economic Co-operation and Development. https://oecd.ai/en/ai-principles
dc.relation.referencesOrganisation for Economic Co-operation and Development. (2024). Recommendation of the Council on Artificial Intelligence. OECD Legal Instruments. https://legalinstruments.oecd.org/en/instruments/OECD-LEGAL-0449
dc.relation.referencesOrganización de las Naciones Unidas para la Educación, la Ciencia y la Cultura [UNESCO]. (2021). Recommendation on the ethics of artificial intelligence. https://unesdoc.unesco.org/ark:/48223/pf0000380455
dc.relation.referencesOrganización para la Cooperación y el Desarrollo Económicos [OCDE]. (2024). Governing with artificial intelligence: Are governments ready? OECD Artificial Intelligence Papers, 20. https://doi.org/10.1787/26324bc2-en
dc.relation.referencesOxford Insights. (2024). Government AI Readiness Index 2024. Oxford Insights. https://oxfordinsights.com/ai-readiness/ai-readiness-index/
dc.relation.referencesParlamento Europeo y el Consejo de la Unión Europea. (2024). Regulation (EU) 2024/1689 of the European Parliament and of the Council of 13 June 2024 laying down harmonised rules on artificial intelligence (Artificial Intelligence Act). Official Journal of the European Union. https://eur-lex.europa.eu/eli/reg/2024/1689/oj/eng
dc.relation.referencesParycek, P., Schmid, V., y Novak, A.-S. (2024). Artificial intelligence (AI) and automation in administrative procedures: Potentials, limitations, and framework conditions. Journal of the Knowledge Economy, 15, 8390–8415. https://doi.org/10.1007/s13132-023-01433-3
dc.relation.referencesRachovitsa, A., y Johann, N. (2022). The human rights implications of the use of AI in the digital welfare state: Lessons learned from the Dutch SyRI case. Human Rights Law Review, 22(2), ngac010. https://doi.org/10.1093/hrlr/ngac010
dc.relation.referencesRechtbank Den Haag. (2020). Nederlands Juristen Comité voor de Mensenrechten et al. v. The State of the Netherlands (ECLI:NL:RBDHA:2020:1878). https://uitspraken.rechtspraak.nl/details?id=ECLI:NL:RBDHA:2020:1878
dc.relation.referencesRoehl, U. B. U. (2023). Automated decision-making and good administration: Views from inside the government machinery. Government Information Quarterly, 40(4), 101864. https://doi.org/10.1016/j.giq.2023.101864
dc.relation.referencesSaxena, D., y Guha, S. (2023). Algorithmic harms in child welfare: Uncertainties in practice, organization, and street-level decision-making. arXiv. https://doi.org/10.48550/arXiv.2308.05224
dc.relation.referencesSaxena, D., Badillo, K., Wisniewski, P. J., y Guha, S. (2021). A framework of high-stakes algorithmic decision-making for the public sector developed through a case study of child- welfare. arXiv. https://doi.org/10.48550/arXiv.2107.03487
dc.relation.referencesSenado Federal do Brasil. (2023). Projeto de Lei n° 2338, de 2023. https://www25.senado.leg.br/web/atividade/materias/-/materia/157233
dc.relation.referencesSuksi, M. (2021). Administrative due process when using automated decision-making in public administration: Some notes from a Finnish perspective. Artificial Intelligence and Law, 29, 87–110. https://doi.org/10.1007/s10506-020-09269-x
dc.relation.referencesUnited Nations High Commissioner for Human Rights. (2021). The right to privacy in the digital age: Report of the United Nations High Commissioner for Human Rights (A/HRC/48/31). https://www.ohchr.org/en/documents/thematic-reports/ahrc4831-right-privacy-digital- age-report-united-nations-high
dc.relation.referencesWachter, S., Mittelstadt, B., y Russell, C. (2021). Why fairness cannot be automated: Bridging the gap between EU non-discrimination law and AI. Computer Law y Security Review, 41, 105567. https://doi.org/10.1016/j.clsr.2021.105567
dc.relation.referencesWilliams, R. A. (2022). Rethinking administrative law for algorithmic decision making. Oxford Journal of Legal Studies, 42(2), 468–494. https://doi.org/10.1093/ojls/gqab032
dc.rightsAttribution-NonCommercial-NoDerivs 2.5 Colombiaen
dc.rights.accessrightsinfo:eu-repo/semantics/openAccess
dc.rights.coarhttp://purl.org/coar/access_right/c_abf2
dc.rights.localAbierto (Texto Completo)spa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/2.5/co/
dc.subject.keywordDue process
dc.subject.keywordAdministrative function
dc.subject.keywordSubstantive equality
dc.subject.keywordArtificial intelligence
dc.subject.keywordState liability
dc.subject.proposalDebido proceso
dc.subject.proposalFunción administrativa
dc.subject.proposalIgualdad material
dc.subject.proposalInteligencia artificial
dc.subject.proposalResponsabilidad estatal
dc.titleInteligencia artificial y función administrativa en América Latina: riesgos jurídico-administrativos y lineamientos para prevenir la reproducción de desigualdades
dc.typemaster thesis
dc.type.coarhttp://purl.org/coar/resource_type/c_db06
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dc.type.driveinfo:eu-repo/semantics/doctoralThesis
dc.type.localTesis de Maestríaspa
dc.type.versioninfo:eu-repo/semantics/acceptedVersion

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