TY - GEN
T1 - Introduction to the Minitrack on AI in Government
AU - Gascó-Hernández, Mila
AU - Carter, Lemuria
AU - Liu, Dapeng
N1 - Publisher Copyright:
© 2025 IEEE Computer Society. All rights reserved.
PY - 2025
Y1 - 2025
N2 - Artificial Intelligence (AI) is profoundly transforming the public sector, driven by technological advancements and the pressing need to address economic constraints. As government agencies strive to enhance service delivery with limited resources, AI has emerged as a pivotal tool, offering increased efficiency, improved decision-making, and superior data analysis capabilities. However, the rise of AI also introduces significant challenges, notably the lack of transparency and accountability inherent in some AI systems, often referred to as “black boxes.” These issues underscore the critical need to design ethical AI solutions that prioritize transparency, fairness, and accountability. This minitrack, part of the Digital Government Track at HICSS, explores the present and future applications of AI in the public sector, highlighting its advantages, complexities, and the imperative for robust governance and oversight. Featuring three accepted papers, the minitrack provides diverse insights-ranging from examining the design principles necessary to foster openness and transparency in generative AI platforms, to reviewing AI implementation in digital government and offering avenues for future research. Collectively, these contributions illuminate the multifaceted research landscape of AI in government, providing a comprehensive understanding of its current state and future direction.
AB - Artificial Intelligence (AI) is profoundly transforming the public sector, driven by technological advancements and the pressing need to address economic constraints. As government agencies strive to enhance service delivery with limited resources, AI has emerged as a pivotal tool, offering increased efficiency, improved decision-making, and superior data analysis capabilities. However, the rise of AI also introduces significant challenges, notably the lack of transparency and accountability inherent in some AI systems, often referred to as “black boxes.” These issues underscore the critical need to design ethical AI solutions that prioritize transparency, fairness, and accountability. This minitrack, part of the Digital Government Track at HICSS, explores the present and future applications of AI in the public sector, highlighting its advantages, complexities, and the imperative for robust governance and oversight. Featuring three accepted papers, the minitrack provides diverse insights-ranging from examining the design principles necessary to foster openness and transparency in generative AI platforms, to reviewing AI implementation in digital government and offering avenues for future research. Collectively, these contributions illuminate the multifaceted research landscape of AI in government, providing a comprehensive understanding of its current state and future direction.
KW - AI
KW - Decision-making
KW - Digital Governance
KW - Government
KW - Public Administration
KW - Public Service
UR - http://www.scopus.com/inward/record.url?scp=105005153181&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:105005153181
T3 - Proceedings of the Annual Hawaii International Conference on System Sciences
SP - 1832
EP - 1833
BT - Proceedings of the 58th Hawaii International Conference on System Sciences, HICSS 2025
A2 - Bui, Tung X.
PB - IEEE Computer Society
T2 - 58th Hawaii International Conference on System Sciences, HICSS 2025
Y2 - 7 January 2025 through 10 January 2025
ER -