INTRODUCTION
DEPARTMENT
ACADEMIC AFFAIRS
ADMISSION
INFORMATION BOARD
Alumni
Department of AI and Public Policy
Department of AI and Public Policy
Department Overview
With the emergence of the Fourth Industrial Revolution, Artificial Intelligence (AI) is expected to drive the digitalization and intelligence of society as a whole, including not only the economy and industry but also politics, society, and culture. Governments around the world are taking the lead in driving and responding to these changes by formulating and implementing national strategies, as well as enhancing their own efforts in utilizing AI for data-driven policy-making, AI-based public services, and regulation and governance of AI.

This department aims to cultivate professionals who have a deep understanding of the characteristics of AI and data in the public sector. They will be equipped with the knowledge and skills to develop AI adoption strategies for public sector organizations and to apply predictive policy-making and provide public services. The department aims to foster specialized personnel who can contribute to the advancement of the public sector in the era of AI and data.
Educational Areas
AI Policy and Governance Track
This track focuses on studying national policies and key policy issues related to the promotion and regulation of AI. Students will learn about AI policy development and governance, gaining insights into the strategic aspects of AI advancement.
Data-based Policy Track
In this track, students will learn about the process of developing predictive policies using big data from both public and private sectors. They will gain knowledge and skills in utilizing data-driven approaches to policy-making.
Public Management and Innovation Track
This track emphasizes the study of public management and innovation. Students will explore topics related to effective management in the public sector, as well as innovative approaches to addressing societal challenges and improving public services.
Students will learn the fundamental contents of all three tracks, and they have the opportunity to focus more intensively on a specific track based on their individual interests.
AI Policy and Governance Data-based Policy Public Management and Innovation
  • - AI Policy and Governance
    (AI National Strategy and Governance, AI and Intelligent Information Society, Theory of the Fourth Industrial Revolution, AI Ecosystem Policy)
  • - National Data Policy
    (Big Data and Information Society, Algorithms and Society)
  • - IT Policy Theory, E-Government Theory
    Government Information Research, Cyber Politics and E-Government,
  • - Current Trends and Responses in IT Policy
    (Cybersecurity Policy, Digital Government and Smart Cities, Global E-Government and ODA, Digital-based Public Innovation, AI and Human: Laboratory of Perception and Behavior)
  • - Research Methodology I & II
  • - Basic Statistical Analysis
  • - Intermediate and Advanced Statistical Analysis
  • - Data-based Policy Case Study
  • - Evidence-based IT Policy Analysis
  • - Data Analysis: Special Lectures
Note: Qualitative analysis methods (content analysis, in-depth interviews, FGI, brainstorming, Delphi analysis, AHP, Q-methodology, etc.)

Quantitative analysis methods (cost-benefit analysis, survey analysis, time series analysis, meta-analysis, panel data analysis, network analysis, text mining, topic analysis, simulation, etc.)
  • - Understanding Public Policy
  • - Special Lectures on Public Policy
  • - Policy Analysis and Evaluation
  • - Theories of Policy Process, Case Studies in Policy
  • - Organizational Behavior and Leadership in Public Administration
  • - Public Management and Economics, . Regulation Policy and Personnel Administration
Note: Learning about policy planning based on theory and evidence, as well as performance management and evaluation techniques for policies, programs, and projects.

Note: Managing Public Performance and Service Innovation using AI and Data
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