Page 91 - Revista Auditoria Pública nº 83

El uso de la IA generativa en la contratación pública para detectar prácticas irregulares

Bibliografía ¡ Gamero Casado, E. y Pérez Guerrero, F. (2023): “In-
teligencia Artificial y Sector Público. Retos, límites y
¡ Aarvik, P. (2019): “Artificial Intelligence – a promising medios”. Valencia: Tirant lo Blanch, 2023.
anti-corruption tool in development settings? Chr. Mi-
chelsen Institute, U4 Report, 2019:1. ¡ García Rodríguez, M. J., Rodríguez Montequín, V., Or-
https://www.u4.no/publications/artificial-intelli- tega Fernández, F. y Villanueva Balsera, J. M. (2019):
gence-a-promising-anti-corruption-tool-in-develop- “Public Procurement Announcements in Spain: Regu-
ment-settings lations, Data Analysis, and Award Price Estimator Using
Machine Learning”. Complexity, vol. 2019, no. v, 2019.
¡ Adam, I. y Fazekas, M. (2021): “Are emerging tech- https://doi.org/10.1155/2019/2360610.
nologies helping win the fight against corruption?
A review of the state of evidence”. Information Eco- ¡ García Rodríguez, M. J., Rodríguez Montequín, V., Or-
nomics and Policy, Volume 57, 2021, 100950, ISSN tega Fernández, F. y Villanueva Balsera, J. M. (2020):
0167-6245. “Bidders Recommender for Public Procurement
https://doi.org/10.1016/j.infoecopol.2021.100950. Auctions Using Machine Learning: Data Analysis, Al-
gorithm, and Case Study with Tenders from Spain”.
¡ Amthauer, J., Fleiß, J., Guggi, F. y Robertson, V. Complexity, vol. 2020, pp. 1–20, Nov. 2020.
(2023): “Ready or not? A systematic review of case https://doi.org/10.1155/2020/8858258.
studies using data-driven approaches to detect re-
al-world antitrust violations,” Computer Law & Secu- ¡ García Rodríguez, M. J., Rodríguez-Montequín,
rity Review, vol. 49, p. 105807. V., Ballesteros-Pérez, P., Love, P. E. D. y Signor, R.
https://doi.org/10.1016/j.clsr.2023.105807 (2022): “Collusion detection in public procurement
auctions with machine learning algorithms”. Automa-
¡ Center for Audit Quality (2024): “Auditing in the Age tion in Construction, vol. 133, p. 104047, enero 2022.
of generative AI” . https://doi.org/10.1016/j.autcon.2021.104047.
https://www.thecaq.org/auditing-in-the-age-of-gene-
rative-ai ¡ Gerli, C. (2024): “How public organizations can use
AI in anti-corruption: What we know so far and why
¡ Ceva, E. y Jiménez, M.C. (2022): “Automating Antico- we need to learn more about it”. Hertie School, Cen-
rruption?”. Ethics and Information Technology (2022) ter for Digital Governance.
24:48 https://www.hertie-school.org/en/digital-governance/
https://doi.org/10.1007/s10676-022-09670-x research/blog/detail/content/how-public-organisa-
tions-can-use-ai-in-anti-corruption-what-we-know-so-
¡ Ebers, M., Poncibó, C. y Zou, M. (2023): “Contracting far-and-why-we-need-to-learn-more-about-it
and Contract Law in the Age of Artificial Intelligence”.
Bloomsbury Publishing, 2023. ¡ Huber, M. e Imhof, D. (2019): “Machine learning with
screens for detecting bid-rigging cartels”. Interna-
¡ European Parliament (2021): “Public procurement tional Journal of Industrial Organization, vol. 65, pp.
contracts”. European Parliament, Fact Sheets on the 277–301, Jul. 2019.
European Union. https://doi.org/10.1016/j.ijindorg.2019.04.002.
https://www.europarl.europa.eu/factsheets/en/
sheet/34/public-procurement-contracts. ¡ Huber, M., Imhof, D. e Ishii, R. (2020): “Transnatio-
nal machine learning with screens for flagging bid-ri-
¡ European Parliament (2024): “The Future of Digitali- gging cartels”. University of Fribourg (Switzerland),
sation in Budgetary Control”. Policy Department for Faculty of Economics and Social Sciences, 2020.
Budgetary Affairs, Directorate-General for Internal https://doc.rero.ch/record/329575/files/WP_
Policies. PE 759.623 – February 2024. SES_519.pdf.
https://www.europarl.europa.eu/thinktank/en/docu-
ment/IPOL_STU(2024)759623 ¡ Huber, M. e Imhof, D. (2023): “Flagging cartel par-
ticipants with deep learning based on convolutional
¡ Gallego, J., Rivero, G. y Martínez, J.D. (2018): “Pre- neural networks”. International Journal of Industrial
venting rather than Punishing: An Early Warning Mo- Organization, p. 102946, Abril 2023.
del of Malfeasance in Public Procurement,” Docu- https://doi.org/10.1016/j.ijindorg.2023.102946.
mentos de Trabajo 16724, Universidad del Rosario.
https://ideas.repec.org/p/col/000092/016724.html ¡ Imhof, D. (2017): “Simple Statistical Screens to De-

91