Workshop on Data-Driven and Artificial Intelligence-Supported Transformation in Public Administration
At the workshop held at the Academy of Public Administration, data-driven approaches, simulation and AI-supported systems' role in public policies, alongside the VL4GoP center, were discussed.
Organized by the Academy of Public Administration, the workshop emphasized the necessity of renewing public administration and policy planning methods in the national digital transformation process. The meeting discussed potential applications of data-driven, simulation, and AI-supported approaches in research, education, and professional development.
The Need for Digital Transformation in Public Administration
Dr. Bui Phuong Dinh, Deputy Director of the Academy of Public Administration, stated that national digital transformation and deep integration require fundamental changes in public administration methods. It was stated that there is a need to transition from an experience-based approach to a system based on data and analytical tools.
Virtual Lab for Governance and Public Policy Center
The workshop examined the research and development of the Virtual Lab for Governance and Public Policy (VL4GoP) Center, which aims to bring together policy research, education, and innovation. The center aims to provide a controlled testing environment.
Data-Driven Governance and Decision Making
Assoc. Prof. Dr. Tran Quang Dieu stated that data-driven governance and evidence-based policy planning provide a transition from manual reporting to analytical decision-making. It was emphasized that artificial intelligence can support analysis processes but cannot replace human responsibility.
Functional Groups and Conditions of the VL4GoP Model
Dr. Doan Van Tinh stated that the center could operate in four main functional groups: student education, public official development, scientific research, and technology transfer. Attention was drawn to the importance of infrastructure and the legal framework.
Implementation and Pilot Testing Recommendations
Experts stated that the center should start from real-world problems and simulation results should be used as reference evidence. It was decided to develop the model through pilot applications and protect the human factor.