aceBridging the gap: Towards an expanded toolkit for AI-driven decision-making in the public sector
AI-driven decision-making systems are becoming instrumental in the public sector, with applications spanning areas like criminal justice, social welfare, financial fraud detection, and public health. While these systems offer great potential benefits to institutional decision-making processes, such as improved efficiency and reliability, these systems face the challenge of aligning machine learning (ML) models with the complex realities of public sector decision-making. In this paper, we examine five key challen…
AI-driven decision-making systems in the public sector can deliver improved efficiency and reliability for institutional decision-making processes.
When deployed in criminal justice, social welfare, fraud detection and public health, standard ML models can produce unreliable and harmful predictions due to misalignment with public-sector realities.
Standard ML approaches may fail in public-sector contexts because their assumptions do not capture operational complexities.
Evidence
- Peer-reviewedGovernment Information Quarterly2024-10-11
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Truvace Impact Record TRV-2026-0354, v1: “Bridging the gap: Towards an expanded toolkit for AI-driven decision-making in the public sector.” Truvace, 2026-07-20. /record/TRV-2026-0354 (accessed at citation time). sha256 cc983b2eeeac3c56…
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