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Artificial Intelligence to Improve Public Budgeting

Series
International Conference for Information Systems
Type
conference paper
Date Issued
2024-12-15
Author(s)
Dominic Santschi  
;
Marc Christopher Grau  
;
Dennis Fehrenbacher  
;
Ivo Blohm  
Abstract
Accurate public budgeting is essential for efficient resource allocation and societal trust. However, recent studies have shown that public budgets often project deficits but have substantial surpluses. This budgetary slack can lead taxpayers to overpay for services not rendered, delay necessary investments, or distort public perceptions of government efficiency. To avoid such unfortunate outcomes, we study how artificial intelligence (AI) can help decision-makers in the public sector with budgeting. We operationalize our research question using a two-step approach. First, we utilize open data from Swiss financial authorities to train and test an AI model. Our preliminary results validate the potential of AI to predict public accounts better than human experts. Second, we study whether decision-makers effectively utilize the AI model in an experimental scenario. The results of our experimental study indicate that human-AI collaboration could indeed support decision-makers to improve public budgeting by reducing budgetary slack.
Accurate public budgeting is essential for efficient resource allocation and societal trust. However, recent studies have shown that public budgets often project deficits but have substantial surpluses. This budgetary slack can lead taxpayers to overpay for services not rendered, delay necessary investments, or distort public perceptions of government efficiency. To avoid such unfortunate outcomes, we study how artificial intelligence (AI) can help decision-makers in the public sector with budgeting. We operationalize our research question using a two-step approach. First, we utilize open data from Swiss financial authorities to train and test an AI model. Our preliminary results validate the potential of AI to predict public accounts better than human experts. Second, we study whether decision-makers effectively utilize the AI model in an experimental scenario. The results of our experimental study indicate that human-AI collaboration could indeed support decision-makers to improve public budgeting by reducing budgetary slack.
Language
English
Keywords
Open Data Utilization
Human-AI Collaboration
Data-driven Governance
Budgeting
HSG Classification
contribution to scientific community
Refereed
Yes
Event Title
International Conference on Informatin Systems
Event Location
Bangkok, Thailand
Event Date
December 15-18
URL
https://www.alexandria.unisg.ch/handle/20.500.14171/121101
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Artificial Intelligence to Improve Public Budgeting.pdf

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d19018a49d22af15427697d135b404ed

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