Trustworthy AI in public administration
The PRO-Trust pipeline for ethical fraud detection in public procurement
Bibliographic Data
| ID | 19233450 |
|---|---|
| Authors | Igor Garcia Ballhausen Sampaio (0000-0002-1890-1451, Universidade Federal Fluminense, corresponding author), Eduardo de Oliveira Andrade, Sérgio de Souza Barbosa Fontes, Flavia Bernardini (0000-0001-8801-827X, Universidade Federal Fluminense), Flávia Cristina Bernardini, José Viterbo (0000-0002-0339-6624, Universidade Federal Fluminense) |
| Year | 2026 |
| Volume | 43 |
| Issue | 3 |
| Pages | 102157 |
| Publication date | 2026-09-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Government Information Quarterly (JOURNAL) |
| Journal identifiers | ISSN: 0740-624X • E-ISSN: 1872-9517 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.giq.2026.102157 |
| OpenAlex | W7163205676 |
| Language | EN |
| References cited | 32 |
Applying Artificial Intelligence (AI) to fraud detection in Public Procurement (PP) has become increasingly relevant due to its ability to process large volumes of data and identify suspicious patterns more efficiently than traditional methods. However, its implementation raises critical ethical concerns regarding respect for human autonomy, prevention of harm, fairness, and explainability. This study investigates these concerns through a four-phase methodology: (i) selection of ethical principles for AI in PP fraud detection, (ii) a Systematic Literature Review (SLR) on current approaches, (iii) cross-analysis and expert validation with senior auditors, and (iv) the construction of PRO-Trust, an ethics-oriented pipeline for constructing trustworthy AI-based fraud detection systems for PPs, based on the findings of the three former stages. PRO-Trust addresses five recurrent ethical challenges — system opacity, lack of user transparency, limitations in explainability tools, lack of operational oversight, and lack of strategic control — connected between tasks we specified for the construction process of AI-based technologies to fraud detection in PP, the responsible actors, and technological strategies to operationalize ethical principles. By doing so, this study contributes to the development of more trustworthy, transparent, and accountable AI-based fraud detection systems in public administration
Constructive fraud · Deception · Procurement · Public trust · Trustworthiness · Ethics and Social Impacts of AI · Explainable Artificial Intelligence (XAI · Mobile Crowdsensing and Crowdsourcing
A Survey of Methods for Explaining Black Box Models
Preferred Reporting Items for Systematic Reviews and Meta-Analyses
Artificial Intelligence Regulation
Public procurement of artificial intelligence systems
Transparency and accountability in digital public services
Do citizens trust trustworthy artificial intelligence? Experimental evidence on the limits of ethical AI measures in government
The strategic use of AI in the public sector
A data quality approach to the identification of discrimination risk in automated decision making systems
Transparency, participation, and accountability practices in open government
The perils and pitfalls of explainable AI
Automation bias in public administration – an interdisciplinary perspective from law and psychology
AI-augmented government transformation
| Citation velocity | historical |
|---|---|
| Highly cited | No |