Inteligencia artificial y función administrativa en América Latina: riesgos jurídico-administrativos y lineamientos para prevenir la reproducción de desigualdades
| dc.contributor.advisor | Cárdenas Sierra, Robinson Ari | |
| dc.contributor.author | Hernández Granados, Diana Shamara | |
| dc.contributor.corporatename | Universidad Santo Tomás | |
| dc.contributor.cvlac | https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001218158 | |
| dc.contributor.googlescholar | https://scholar.google.com/citations?user=4IMyBP0AAAAJ&hl=es | |
| dc.contributor.orcid | https://orcid.org/0000-0002-4773-0233 | |
| dc.date.accessioned | 2026-08-06T14:20:10Z | |
| dc.date.available | 2026-08-06T14:20:10Z | |
| dc.date.issued | 2026-08-05 | |
| dc.description | El 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.abstract | The 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.degreelevel | Maestría | spa |
| dc.description.degreename | Maestría en Derecho Administrativo | spa |
| dc.description.domain | http://www.ustatunja.edu.co/investigacion | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.citation | Hernández 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.instname | instname:Universidad Santo Tomás | spa |
| dc.identifier.reponame | reponame:Repositorio Institucional Universidad Santo Tomás | spa |
| dc.identifier.repourl | repourl:https://repository.usta.edu.co | spa |
| dc.identifier.uri | http://hdl.handle.net/11634/73825 | |
| dc.language.iso | spa | |
| dc.publisher | Universidad Santo Tomás | spa |
| dc.publisher.branch | CRAI-USTA Tunja | |
| dc.publisher.faculty | Facultad de Derecho | spa |
| dc.publisher.program | Facultad de Derecho | spa |
| dc.relation.references | Agencia 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.references | Ahn, 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.references | Alon, 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.references | Banco Mundial. (2021). Informe sobre el desarrollo mundial 2021: Datos para una vida mejor. World Bank. https://www.worldbank.org/en/publication/wdr2021 | |
| dc.relation.references | Cobbe, 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.references | Comisión Económica para América Latina y el Caribe [CEPAL]. (2025). Índice Latinoamericano de Inteligencia Artificial (ILIA) 2025. https://hdl.handle.net/11362/82514 | |
| dc.relation.references | Comisión Europea. (2026). AI Act. Shaping Europe’s Digital Future. https://digital- strategy.ec.europa.eu/en/policies/regulatory-framework-ai | |
| dc.relation.references | Consejo 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.references | Corte Constitucional de Colombia. (2021). Sentencia C-162 de 2021. https://www.funcionpublica.gov.co/eva/gestornormativo/norma.php?i=173213 | |
| dc.relation.references | Covilla, 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.references | Cruz, 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.references | de 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.references | Department 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.references | Departamento 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.references | Díaz, 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.references | European 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.references | Gerards, 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.references | Green, 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.references | Harper, 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.references | Information Commissioner’s Office. (2025). Artificial intelligence. https://ico.org.uk/for- organisations/uk-gdpr-guidance-and-resources/artificial-intelligence/ | |
| dc.relation.references | Kaminski, 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.references | Langer, 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.references | Levy, 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.references | Levy, 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.references | Loi, 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.references | Lyons, 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.references | Mantelero, 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.references | Metcalf, 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.references | Ministério 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.references | Ministerio 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.references | Mokander, 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.references | National 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.references | OECD.AI. (2026). OECD AI Principles overview. Organisation for Economic Co-operation and Development. https://oecd.ai/en/ai-principles | |
| dc.relation.references | Organisation 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.references | Organización 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.references | Organización 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.references | Oxford Insights. (2024). Government AI Readiness Index 2024. Oxford Insights. https://oxfordinsights.com/ai-readiness/ai-readiness-index/ | |
| dc.relation.references | Parlamento 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.references | Parycek, 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.references | Rachovitsa, 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.references | Rechtbank 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.references | Roehl, 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.references | Saxena, 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.references | Saxena, 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.references | Senado Federal do Brasil. (2023). Projeto de Lei n° 2338, de 2023. https://www25.senado.leg.br/web/atividade/materias/-/materia/157233 | |
| dc.relation.references | Suksi, 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.references | United 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.references | Wachter, 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.references | Williams, 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.rights | Attribution-NonCommercial-NoDerivs 2.5 Colombia | en |
| dc.rights.accessrights | info:eu-repo/semantics/openAccess | |
| dc.rights.coar | http://purl.org/coar/access_right/c_abf2 | |
| dc.rights.local | Abierto (Texto Completo) | spa |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/2.5/co/ | |
| dc.subject.keyword | Due process | |
| dc.subject.keyword | Administrative function | |
| dc.subject.keyword | Substantive equality | |
| dc.subject.keyword | Artificial intelligence | |
| dc.subject.keyword | State liability | |
| dc.subject.proposal | Debido proceso | |
| dc.subject.proposal | Función administrativa | |
| dc.subject.proposal | Igualdad material | |
| dc.subject.proposal | Inteligencia artificial | |
| dc.subject.proposal | Responsabilidad estatal | |
| dc.title | Inteligencia artificial y función administrativa en América Latina: riesgos jurídico-administrativos y lineamientos para prevenir la reproducción de desigualdades | |
| dc.type | master thesis | |
| dc.type.coar | http://purl.org/coar/resource_type/c_db06 | |
| dc.type.coarversion | http://purl.org/coar/version/c_ab4af688f83e57aa | |
| dc.type.drive | info:eu-repo/semantics/doctoralThesis | |
| dc.type.local | Tesis de Maestría | spa |
| dc.type.version | info:eu-repo/semantics/acceptedVersion |
Archivos
Bloque original
1 - 3 de 3
Cargando...
- Nombre:
- 2026DianaHernández
- Tamaño:
- 960.84 KB
- Formato:
- Adobe Portable Document Format
Cargando...
- Nombre:
- Autorización estudiante
- Tamaño:
- 116.88 KB
- Formato:
- Adobe Portable Document Format
Cargando...
- Nombre:
- Autorización facultad
- Tamaño:
- 358.89 KB
- Formato:
- Adobe Portable Document Format
Bloque de licencias
1 - 1 de 1
Cargando...
- Nombre:
- license.txt
- Tamaño:
- 807 B
- Formato:
- Item-specific license agreed upon to submission
- Descripción:

