Smart Governance Frameworks Using Emerging Technologies for Efficient Public Administration

Abstract

The challenge for public administration in the world is to deliver increasingly more services to the people at ever-increasing speed, transparency, accessibility, and inclusiveness, with limited resources and outdated structures. Traditional e-government programs are the target of this paper. Traditional e-government programs have not been successful in changing the decision-making logic that underlies the processes. Smart governance is viewed in this paper as a socio-technical reorganization of the state and not as something that can be realized by a simple digitization process. It proposes a multi-level framework of a Smart Governance Framework (SGF) which includes five levels: data ingestion, data processing, data intelligence, service delivery, and citizen feedback loop. A layer of cross-cutting data governance, data interoperability, and ethical oversight is woven throughout all five. The paper is based on a literature review of existing studies on the smart city, public sector application of artificial intelligence (AI), and the delivery of digital services. It pinpoints regular administrative delays, sets rules on data sharing between teams, and matches certain developing technologies to these delays. The framework is then put to the test in illustrative municipal and federal deployment scenarios. In these situations, the processing time, error and grievance resolution rates, and legacy systems, capital constraints, and workforce skill resistance are likely to improve. Finally, algorithmic decision-making and the accountability paradox, digital exclusion, and the importance of data sovereignty and cyber-resilience are explored. This culminates in some policy suggestions and an agenda for future research.