Gobernanza ética de la inteligencia artificial en la administración pública: una revisión integrativa de la literatura (2021–2025)
DOI:
https://doi.org/10.36517/contextus.2026.96781Palabras clave:
inteligencia artificial; IA generativa; administración pública; gobernanza ética; la confianza ciudadana.Resumen
Contextualización: La Inteligencia Artificial (IA), en particular la IA generativa, se está consolidando como motor de transformación en la Administración Pública, prometiendo eficiencia operativa pero planteando riesgos significativos para la discrecionalidad y la equidad.
Objetivo: Este estudio busca analizar, mediante una revisión integradora, cómo la producción académica reciente (2021-2025) aborda y propone vías para la gobernanza ética de la IA en el sector público.
Método: Siguiendo el protocolo de Fink (2014), se analizaron 22 artículos de alto impacto de la base de datos Web of Science.
Resultados: Los resultados revelan una rápida expansión de la literatura sobre el tema, marcada por tres ejes temáticos: (i) la tensión entre la agilidad algorítmica y el juicio humano; (ii) la reacción regulatoria tardía ante la opacidad de los sistemas automatizados; y (iii) la centralidad de la confianza ciudadana como indicador de éxito. La bibliometría pone de relieve una geopolítica multipolar del conocimiento, con China y Brasil desempeñando un papel protagónico en los enfoques pragmáticos de control.
Conclusiones: El estudio contribuye al proponer directrices estructurales para la implementación de la IA en el sector público. Se concluye que garantizar la ética de la IA en la administración pública no solo depende de la tecnología, sino también de la alfabetización digital y la construcción de un ecosistema de gobernanza híbrido, que combine la regulación normativa, la auditoría técnica y la supervisión humana obligatoria (intervención humana) en las decisiones críticas.
Referencias
Adobor, H., & Yawson, R. (2023). The promise of artificial intelligence in combating public corruption in the emerging economies: A conceptual framework. Science and Public Policy, 50(3), 355–370. https://doi.org/10.1093/scipol/scac068
ANPD. (2024). Inteligência artificial generativa. https://www.gov.br/anpd/pt-br/centrais-de-conteudo/documentos-tecnicos-orientativos/radar_tecnologico_ia_generativa_anpd.pdf
Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J. D., Dhariwal, P., … Amodei, D. (2020). Language models are few-shot learners. Advances in Neural Information Processing Systems, 33, 1877–1901. https://papers.nips.cc/paper_files/paper/2020/hash/1457c0d6bfcb4967418bfb8ac142f64a-Abstract.html
Bullock, J. B. (2019). Artificial intelligence, discretion, and bureaucracy. The American Review of Public Administration, 49(7), 751–761. https://doi.org/10.1177/0275074019856123
Chandra, Y., & Feng, N. (2025). Algorithms for a new season? Mapping a decade of research on the artificial intelligence-driven digital transformation of public administration. Public Management Review, 28(3), 620–654. https://doi.org/10.1080/14719037.2025.2450680
Comissão Europeia. (2025). Regulamento de Inteligência Artificial da União Europeia: Proposta de 2021 para uso confiável de IA. https://eur-lex.europa.eu/legal-content/PT/TXT/HTML/?uri=CELEX:52021PC0206
Cruz, F. B., Britto, M. C. S., Moreira, G. M., & Britto, A. S., Junior. (2022). Robôs substituem juízes? O estado da arte da inteligência artificial no judiciário brasileiro. Revista Antinomias, 3(1), 8–41.
Façanha, V. S., Souza, A. A., Júnior, Moraes, A. F. M., & Mendes, S. A. T. (2024). Inteligência Artificial na administração pública: Perspectivas e impactos na sociedade. International Journal of Scientific Management and Tourism, 10(5), e1098. https://doi.org/10.55905/ijsmtv10n5-004
Fajardo, B., & Neiva, S. (2025). ‘Malha Fina de Convênios’: An AI application for auditing in the Brazilian federal government. Public Money & Management, 1–12. https://doi.org/10.1080/09540962.2025.2499704
Fang, X., Zhou, H., & Chen, S. (2025). A replication of “Explaining why the computer says no: Algorithmic transparency affects the perceived trustworthiness of automated decision-making”. Public Administration, 103(4), 1232–1252. https://doi.org/10.1111/padm.70015
Fink, A. (2014). Conducting research literature reviews: From the internet to paper (4th ed.). Los Angeles London; New Delhi Singapore Washington DC: SAGE.
Floridi, L., & Chiriatti, M. (2020). GPT-3: Its nature, scope, limits, and consequences. Minds and Machines, 30(4), 681–694. https://doi.org/10.1007/s11023-020-09548-1
Government Of Canada, Treasury Board of Canada. (2025). Directive on automated decision-making. https://www.tbs-sct.canada.ca/pol/doc-eng.aspx?id=32592
Grimmelikhuijsen, S. (2023). Explaining why the computer says no: Algorithmic transparency affects the perceived trustworthiness of automated decision-making. Public Administration Review, 83(2), 241–262. https://doi.org/10.1111/puar.13483
Juárez-Merino, M. (2025). Artificial intelligence and citizenship in latin american governments. Public Administration Issues, 71–86. https://doi.org/10.17323/1999-5431-2025-0-5-71-86
Laux, J., Wachter, S., & Mittelstadt, B. (2024). Trustworthy artificial intelligence and the European Union AI act: On the conflation of trustworthiness and acceptability of risk. Regulation & Governance, 18(1), 3–32. https://doi.org/10.1111/rego.12512
Liang, Z., Li, Y., & Chen, T. (2025). When AI fails, who gets the blame? Citizens’ attribution patterns in AI-induced public service failures. Journal of Chinese Governance, 10(4), 630–659. https://doi.org/10.1080/23812346.2025.2528005
MCTI. (2021). Estratégia Brasileira de Inteligência Artificial (EBIA). https://www.gov.br/mcti/pt-br/acompanhe-o-mcti/transformacaodigital/arquivosinteligenciaartificial/ebia-diagramacao_4-979_2021.pdf
Mencke, W., Gomes, R., & Xavier, F. (2024). Impacts of AI-based anti-corruption audits on risk aversion in decision-making: A case study of the Brazilian ALICE tool. Global Public Policy and Governance, 4(3), 273–286. https://doi.org/10.1007/s43508-024-00098-1
Neves, J. B. J., & Romão, A. L. S. (2024). Adoção de IA na Administração Pública: Do tecnicismo à vantagem competitiva e à confiança dos cidadãos. Revista del CLAD Reforma y Democracia, 90, 25–53. https://doi.org/10.69733/clad.ryd.n90.a378
Niaradi, G. A., & Nascimento, N. N. (2023). Inteligência artificial e os riscos nas fiscalizações do controle externo. Suprema - Revista de Estudos Constitucionais, 3(1), 439–469. https://doi.org/10.53798/suprema.2023.v3.n1.a218
Nieuwenhuizen, E. N., Meijer, A. J., Bex, F. J., & Grimmelikhuijsen, S. G. (2025). Explanations increase citizen trust in police algorithmic recommender systems: Findings from two experimental tests. Public Performance & Management Review, 48(3), 590–625. https://doi.org/10.1080/15309576.2024.2443140
Noordt, C., Medaglia, R., & Tangi, L. (2025). Policy initiatives for Artificial Intelligence-enabled government: An analysis of national strategies in Europe. Public Policy and Administration, 40(2), 215–253. https://doi.org/10.1177/09520767231198411
OECD. (2024). Recommendation of the Council on Artificial Intelligence. https://legalinstruments.oecd.org/en/instruments/oecd-legal-0449
Oliveira, R. N. D., & Dias, T. F. (2023). Inteligência Artificial no Setor Público: Estudo de casos de aplicação da IA na Administração Pública Brasileira. https://sbap.org.br/ebap-2023/anais/documento_final-166.pdf
Paglieri, L., Costumato, L., & Savignon, A. B. (2025). Does artificial intelligence improve social equity in public services? A systematic literature review on opportunities and pitfalls. International Journal of Public Sector Management. https://doi.org/10.1108/IJPSM-10-2024-0333
Plantinga, P., Shilongo, K., Mudongo, O., Umubyeyi, A., Gastrow, M., & Razzano, G. (2024). Responsible artificial intelligence in Africa: Towards policy learning. Data & Policy, 6, e72. https://doi.org/10.1017/dap.2024.60
Robles, P., & Mallinson, D. J. (2025). Artificial intelligence technology, public trust, and effective governance. Review of Policy Research, 42(1), 11–28. https://doi.org/10.1111/ropr.12555
Ruvalcaba-Gomez, E. A. (2025). Systematic and axiological capacities in artificial intelligence applied in the public sector. Public Policy and Administration, 40(2), 351–371. https://doi.org/10.1177/09520767231170321
Santos, M. (1994). Técnica espaço tempo – Globalização e meio técnicocientífico-informacional. https://reverbe.net/cidades/wp-content/uploads/2011/livros/tecnica-espaco-tempo-milton-santos.pdf
Santos, M., & Marques, M. C. (2002). A natureza do espaço: Técnica e tempo, razão e emoção (4th ed.). São Paulo, SP: EDUSP.
Schiff, D. S., Schiff, K. J., & Pierson, P. (2022). Assessing public value failure in government adoption of artificial intelligence. Public Administration, 100(3), 653–673. https://doi.org/10.1111/padm.12742
SGD, & SERPRO. (2025). IA Generativa no Serviço Público. https://www.gov.br/governodigital/pt-br/infraestrutura-nacional-de-dados/inteligencia-artificial-1/publicacoes/guia-ia-generativa
Tao, L., Wan, J., & Wen, B. (2025). The effects of artificial intelligence and victims’ deservingness information on citizens’ blame attribution towards administrative errors. Public Management Review, 27(12), 3104–3124. https://doi.org/10.1080/14719037.2024.2411632
Teixeira, R. L. C. J. (2023). Diretrizes ético-jurídicas para o design e uso de inteligência artificial na administração pública. Workshop sobre as Implicações da Computação na Sociedade (WICS), 123–130. https://doi.org/10.5753/wics.2023.229812
Toledo, A. T., & Mendonça, M. (2023). A aplicação da inteligência artificial na busca de eficiência pela administração pública. Revista do Serviço Público (RSP), 74(2), 410–438. https://doi.org/10.21874/rsp.v74i2.6829
UK Government. (2023). Ethics, transparency and accountability framework for automated decision-making. https://www.gov.uk/government/publications/ethics-transparency-and-accountability-framework-for-automated-decision-making/ethics-transparency-and-accountability-framework-for-automated-decision-making
Valle-Cruz, D., Garcia-Contreras, R., & Gil-Garcia, J. R. (2024). Exploring the negative impacts of artificial intelligence in government: The dark side of intelligent algorithms and cognitive machines. International Review of Administrative Sciences, 90(2), 353–368. https://doi.org/10.1177/00208523231187051
Willems, J., Schmid, M. J., Vanderelst, D., Vogel, D., & Ebinger, F. (2023). AI-driven public services and the privacy paradox: Do citizens really care about their privacy? Public Management Review, 25(11), 2116–2134. https://doi.org/10.1080/14719037.2022.2063934
Young, M. M., Himmelreich, J., Bullock, J. B., & Kim, K.-C. (2021). Artificial intelligence and administrative evil. Perspectives on Public Management and Governance, 4(3), 244–258. https://doi.org/10.1093/ppmgov/gvab006
Yuan, Q., & Chen, T. (2025). Holding ai-based systems accountable in the public sector: A systematic review. Public Performance & Management Review, 48(6), 1389–1422. https://doi.org/10.1080/15309576.2025.2469784
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