Hacia una gobernanza algorítmica transparente: auditoría de sesgo. Estudio de caso.

• Bustelo Gracia, José Luis ^[1]
  1. [1] Digital Business and Law School
• Localización: Cuadernos de Gobierno y Administración Pública, ISSN 2341-3808, Vol. 12, Nº. 1, 2025
• Idioma: español
• DOI: 10.5209/cgap.97604
• Enlaces
  • Texto completo
• Dialnet Métricas: 1 Cita
• Resumen
  • español

    Este artículo explora la necesidad de implementar auditorías de sesgo en sistemas algorítmicos, particularmente en el contexto de la gobernanza pública. Con el incremento del uso de la inteligencia artificial (IA) en la toma de decisiones gubernamentales, surge la preocupación sobre la transparencia y equidad de estos sistemas. Se analizan diversas normativas europeas, como el Reglamento de Inteligencia Artificial (AI Act), y estudios de caso que evidencian la persistencia de sesgos en algoritmos, destacando la importancia de un enfoque proactivo en la regulación y la implementación de auditorías sistemáticas. Además, se discuten las implicaciones éticas y sociales de la gobernanza algorítmica y se proponen soluciones para mitigar los riesgos asociados.

      Palabras Clave Gobernanza algorítmica, transparencia, auditoría de sesgo, inteligencia artificial.

  • English

    This article examines the necessity of implementing bias audits in algorithmic systems, particularly within the context of public governance. With the increasing use of artificial intelligence (AI) in governmental decision-making, concerns about the transparency and fairness of these systems have arisen. The paper analyzes various European regulations, such as the Artificial Intelligence Act (AI Act), and case studies that highlight the persistence of biases in algorithms, emphasizing the importance of a proactive regulatory approach and systematic audits. Additionally, it discusses the ethical and social implications of algorithmic governance and proposes solutions to mitigate associated risks.

      Keywords Algorithmic governance, transparency, bias audit, artificial intelligence.

• Referencias bibliográficas
  • Aguilar Villanueva L. F. (2014). Las dimensiones y los niveles de gobernanza. Cuadernos de Gobierno y Administración Pública, 1(1), 11-36....
  • Ajunwa, I. (2019). “The Auditing Imperative for Automated Hiring”, Harvard Journal of Law & Technology, 34 (forthcoming 2021). https://ssrn.com/abstract=3437631...
  • Albaroudi, E., Mansouri, T. and Alameer, A. (2024). “A comprehensive review of AI techniques for addressing algorithmic bias in job hiring”,...
  • Arellano Gault D. (2014). ¿Uno o varios tipos de gobernanza? Más allá de la gobernanza como moda: la prueba del tránsito organizacional. Cuadernos...
  • Bartley, N., Abeliuk, A., Ferrara, E. and Lerman, K. (2021). “Auditing algorithmic bias on Twitter”, Proceedings of the 2021 Web Conference....
  • Beduschi, A. (2024). “Synthetic data protection: Towards a paradigm change in data regulation?”, Big Data & Society, 11(1), p. 20539517241231277....
  • Binns, R. (2018). “Fairness in machine learning: Lessons from political philosophy”, Proceedings of the 2018 Conference on Fairness, Accountability,...
  • Bouderhem, R. (2024). “Shaping the future of AI in healthcare through ethics and governance”, Humanities and Social Sciences Communications,...
  • Busuioc, M., Curtin, D. and Almada, M. (2023). “Reclaiming transparency: contesting the logics of secrecy within the AI Act”, European Law...
  • Cath, C. (2018). “Governing artificial intelligence: ethical, legal and technical opportunities and challenges”, Philosophical Transactions...
  • Calero Valdez, A., Heine, M., Franke, T., Jochems, N., Jetter, H.-C. and Schrills, T. (2024). “The European commitment to human-centered technology:...
  • Conitzer, V., Hadfield, G.K. and Vallor, S. (2022). “Technical perspective: The impact of auditing for algorithmic bias”, Communications of...
  • Crespo-González J., Vicente Vicente M. J. ., Saudade Baltazar M. . y Valmorisco Pizarro S. . (2024). Profesorado universitario e ia: ¿una...
  • Dekker, R., Koot, P., Birbil, S. and van Embden, A.M. (2022). “Co-designing algorithms for governance: Ensuring responsible and accountable...
  • Diakopoulos, N. (2016). “Accountability in algorithmic decision making”, Communications of the ACM, 59(2), pp. 56-62. DOI: 10.1145/2844110.
  • Engelmann, A. (2023). “Algorithmic transparency as a fundamental right in the democratic rule of law”, Brazilian Journal of Law, Technology...
  • García Magariño S. (2016). Un cuestionamiento de los supuestos que vertebran la sociedad moderna en búsqueda de nuevos modelos de gobernanza:...
  • Giest, S. and Grimmelikhuijsen, S. (2020). “Introduction to special issue algorithmic transparency in government: Towards a multi-level perspective”,...
  • Giunchiglia, F., Otterbacher, J., Kleanthous, S., Batsuren, K., Bogina, V., Kuflik, T. and Shulner Tal, A. (2021). “Towards algorithmic transparency:...
  • Groves, L., Metcalf, J., Kennedy, A., Vecchione, B. and Strait, A. (2024). “Auditing work: Exploring the New York City algorithmic bias audit...
  • Gstrein, O., Haleem, N. and Zwitter, A. (2024). “General-purpose AI regulation and the European Union AI Act”, Internet Policy Review, 3,...
  • Guerrero García A. L. (2023). Cuando hablamos de capacidad burocrática ¿de qué hablamos? Una revisión teórica y empírica del concepto. Cuadernos...
  • Gyevnar, B., Ferguson, N. and Schafer, B. (2023). “Bridging the transparency gap: What can explainable AI learn from the AI Act?”, Frontiers...
  • Hickok, M., Dorsey, C., O’Brien, T., Baur, D., Ingram, K. and Chauhan, C. (2022). “Case study: The distilling of a biased algorithmic decision...
  • Holstein, K., Wortman, V., Daumé III, H., Dudik, M., and Wallach, H. (2019). “Improving fairness in machine learning systems: What do industry...
  • Kharitonova, Y., Malik, N.S. and Yang, T. (2023). “The legal issue of deterrence of algorithmic control of digital platforms: The experience...
  • Lam, K., Lange, B., Blili-Hamelin, B., Davidović, J., Brown, S. and Hasan, A. (2024). “A framework for assurance audits of algorithmic systems”,...
  • Laux, J., Wachter, S. and Mittelstadt, B. (2023). “Trustworthy artificial intelligence and the European Union AI Act: On the conflation of...
  • Lepri, B., Oliver, N., Letouzé, E., Pentland, A. and Vinck, P. (2018). “Fair, transparent, and accountable algorithmic decision-making processes”,...
  • Mashhadi, A., Zolyomi, A. and Quedado, J. (2022). “A case study of integrating fairness visualization tools in machine learning education”,...
  • Mensah, G.B. (2023). Artificial intelligence and ethics: A comprehensive review of bias mitigation, transparency, and accountability in AI...
  • Mittelstadt, B.D., Allo, P., Taddeo, M., Wachter, S. and Floridi, L. (2016). “The ethics of algorithms: Mapping the debate”, Big Data &...
  • Percy, C., Dragicevic, S., Sarkar, S. and Garcez, A. (2021). “Accountability in AI: From principles to industry-specific accreditation”, AI...
  • Qureshi, N.I., Choudhuri, S.S., Nagamani, Y., Varma, R. and Shah, R. (2024). “Ethical considerations of AI in financial services: Privacy,...
  • Sovrano, F., Sapienza, S., Palmirani, M. and Vitali, F. (2022). “Metrics, explainability and the European AI Act proposal”, Journal of Future...
  • Springer, A. and Whittaker, S. (2021). “Making transparency clear: The dual importance of explainability and auditability”, Proceedings of...
  • Turksen, U., Benson, V. and Adamyk, B. (2024). “Legal implications of automated suspicious transaction monitoring: Enhancing integrity of...
  • Wachter, S., Mittelstadt, B. and Floridi, L. (2017). “Transparent, explainable, and accountable AI for robotics”, Science Robotics, 2(6),...
  • Wörsdörfer, M. (2023). “Mitigating the adverse effects of AI with the European Union’s artificial intelligence act: Hype or hope?”, Journal...
  • Xiang, F., Zhang, X., Cui, J., Carlin, M. and Song, Y. (2022). “Algorithmic bias in student success prediction models: Two case studies”,...
  • Zharova, A. (2023). “Achieving algorithmic transparency and managing risks of data security when making decisions without human interference:...