Valle-Cruz, D., Gil-Garcia, J. R., & Sandoval-Almazan, R. (2024). Artificial intelligence algorithms and applications in the public sector: a systematic literature review based on the PRISMA approach. Research Handbook on Public Management and Artificial Intelligence, 8-26. (acceso abierto) Open Access en https://doi.org/10.4337/9781802207347.00010
Abstract:
abstract
The use of artificial intelligence (AI) algorithms and applications in the public sector has been significantly increasing worldwide. The promise of AI involves massive automation, efficiency, error reduction, and the generation of public value. Despite the potential benefits promised by AI algorithms and applications, their realisation in the public sector is not always clear. Through a systematic literature review based on the PRISMA approach, this chapter aims to answer two research questions: (1) Which are the AI algorithms and applications in the public sector that are most studied in the scientific literature? and (2) What are some of the positive and negative consequences from implementing intelligent algorithms and cognitive machines in the public sector? The results showed a clear dominance and high visibility of machine learning techniques in AI projects in the public sector. Some AI potential negative consequences identified in the literature review are discrimination against certain racial groups and systematic inequities for the most economically or socially vulnerable groups. Most studied topics in current research about AI in government are related to AI governance, transparency, and explainability.