TY - GEN
T1 - Can Artificial Intelligence Help Optimize the Public Budgeting Process? Lessons about Smartness and Public Value from the Mexican Federal Government
AU - Fernandez-Cortez, Vanessa
AU - Valle-Cruz, David
AU - Gil-Garcia, J. Ramon
N1 - Publisher Copyright: © 2020 IEEE.
PY - 2020/4
Y1 - 2020/4
N2 - Public budgeting is at the core of any government, since decisions about how to use resources affect all areas of public policy and government programs. With emerging technologies like artificial intelligence, new opportunities may exist to improve the public budgeting process. Although recent research has focused on many topics related to public budgeting, there is still a gap in terms of our knowledge about the potential role of artificial intelligence techniques. While the potential advantages of using intelligent algorithms for optimization in the private sector have been studied, there are also potential benefits that are unique to the public sector, particularly in terms of improved decision-making. This study proposes a methodology based on artificial intelligence to explore the optimization of the Mexican federal government's public budget distribution. The main outcomes explored are related to social development, economic development, government, and non-programmed budget items. The findings indicate that investment in social development in Mexico should be increased and the non-program-based budget should be reduced. We acknowledge that many other factors influence the allocation of public budgets to different policy domains and specific government programs, including political and environmental variables, but think it is useful to have a proposed 'optimal' solution to better understand the differences between policy priorities and budget allocations and the causes of those differences.
AB - Public budgeting is at the core of any government, since decisions about how to use resources affect all areas of public policy and government programs. With emerging technologies like artificial intelligence, new opportunities may exist to improve the public budgeting process. Although recent research has focused on many topics related to public budgeting, there is still a gap in terms of our knowledge about the potential role of artificial intelligence techniques. While the potential advantages of using intelligent algorithms for optimization in the private sector have been studied, there are also potential benefits that are unique to the public sector, particularly in terms of improved decision-making. This study proposes a methodology based on artificial intelligence to explore the optimization of the Mexican federal government's public budget distribution. The main outcomes explored are related to social development, economic development, government, and non-programmed budget items. The findings indicate that investment in social development in Mexico should be increased and the non-program-based budget should be reduced. We acknowledge that many other factors influence the allocation of public budgets to different policy domains and specific government programs, including political and environmental variables, but think it is useful to have a proposed 'optimal' solution to better understand the differences between policy priorities and budget allocations and the causes of those differences.
KW - Artificial Intelligence
KW - Genetic Algorithms
KW - Mexico
KW - Optimization
KW - Public Budget
KW - Smartness
UR - https://www.scopus.com/pages/publications/85089141072
U2 - 10.1109/ICEDEG48599.2020.9096745
DO - 10.1109/ICEDEG48599.2020.9096745
M3 - Conference contribution
T3 - 2020 7th International Conference on eDemocracy and eGovernment, ICEDEG 2020
SP - 312
EP - 315
BT - 2020 7th International Conference on eDemocracy and eGovernment, ICEDEG 2020
A2 - Teran, Luis
A2 - Pincay, Jhonny
A2 - Portmann, Edy
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th International Conference on eDemocracy and eGovernment, ICEDEG 2020
Y2 - 22 April 2020 through 24 April 2020
ER -