Artificial Intelligence to Improve Public Budgeting

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.

Publication Details

Journal
Journal of the Association for Information Systems
Published
2024-12-15
Citations
1
Primary Topic
Bryophyte Studies and Records
Type
article
Field-Weighted Citation Impact
1.03
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article

Artificial Intelligence to Improve Public Budgeting

1 citations
Journal of the Association for Information Systems
Bryophyte Studies and Records
1.03
article

Artificial Intelligence to Improve Public Budgeting

article en
1 citations

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.

Journal of the Association for Information Systems
Partnerships for the goals
Openalex Percentile: Top 15%
Bryophyte Studies and Records
1.03
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