Shape the Future by Connecting Human Insight with Data Intelligence
The Human Science & Society program is a pioneering English-track interdisciplinary major designed to cultivate future leaders who can solve complex global challenges. By integrating deep humanistic insights with cutting-edge computational tools, we prepare you to lead innovation in an AI-driven world.
What is Human Science & Society?
This major focuses on understanding the complex contexts of human communication, learning, and social interaction. By combining domain expertise in social sciences with information-based analytical technologies (AI, Data Modeling, and Algorithms), students learn to design creative strategies for solving real-world problems.
Educational Goals
• Contextual Problem Solving: Develop the core competency to discover and define problems within social, technical, and cultural environments.
• Digital Integration: Master technical tools like AI and data processing as means to enhance human-centered problem solving.
• Global Leadership: Grow into a "Global Creative Innovation Leader" capable of leading sustainable social innovation.
Curriculum Structure: Computational Core + Domain Pathways
Designed to cultivate future-ready interdisciplinary leaders, the program places computational and data-driven approaches at its core, while empowering students to tailor their academic pathway through domain-specific electives across the humanities and social sciences.
As technological paradigms continue to evolve, the curriculum will be continuously updated to reflect emerging data- and AI-driven methodologies alongside societally significant topics across diverse domains.
I. Core Foundations (Required)
Building the Computational Backbone
The Core Foundations establish the program’s analytical backbone. Students develop essential competencies in AI methodologies, data analytics, and structured knowledge design—skills that form the basis of interdisciplinary problem solving in a data-driven world. These shared foundations ensure that all students acquire the computational literacy required to navigate complex societal challenges.
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Host Department |
Course Title |
Credits |
Focus Area |
||
|
Global Convergence |
Introduction to Natural Language Processing |
3 |
Applied AI and language data processing |
||
|
Business Administration |
|
3 |
Data preprocessing, visualization, and R-based modeling |
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|
Library & Information Science |
Principles of Metadata |
3 |
Structured data and interoperability |
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Library & Information Science |
Domain Analysis for Information Organization |
3 |
Conceptual modeling and knowledge organization |
||
|
English Language & Literature |
Data Science for Language Analysis |
3 |
LLM prompts, computational text analysis, human-AI interaction |
II. Domain Exploration (Elective Tracks)
Applying AI to Real-World Systems
Building on this foundation, the Domain Exploration tracks situate computational tools within three key societal spheres: governance and public systems, economic and industrial environments, and education and communication ecosystems.
Students learn to translate data-driven insights into responsible, human-centered innovation—whether shaping public policy, transforming markets, or redesigning learning and communication in the age of AI. Electives can be selected in alignment with individual interests and career aspirations.
A. Society & Governance
|
Host Department |
Course Title |
Credits |
Focus Area |
|
Sociology |
Gender and Power |
3 |
Sociological knowledge on gender and sexuality |
|
Public Administration |
Digital Government and New Governance Models |
3 |
Agile government and civic tech-based problem solving |
|
Public Administration |
Strategic Planning and Performance Management |
3 |
Strategic tools for public and non-profit organizations |
|
Public Administration |
Data-Driven Environmental and Energy Governance and Empathy-Intelligent Policy Innovation |
3 |
Sustainable policy innovation using platform governance |
B. Economy & Industry
|
Host Department |
Course Title |
Credits |
Focus Area |
||
|
Consumer Science |
Digital Divide and Consumer Inequality |
3 |
Socioeconomic inequality in digital environments |
||
|
|
Understanding of Public Finance |
3 |
Public resource allocation and economic systems |
C. Education & Communication
|
Host Department |
Course Title |
Credits |
Focus Area |
|
German Language & Literature |
AI and Language Education |
3 |
AI-based instructional design and Edutech |
|
Education |
Learning Science |
3 |
Cognitive science, educational psychology, AI in learning |
|
Global Convergence |
Data Unfolded Critical Interfaces and Material Practices |
3 |
International collaborative media art |
Career Opportunities
Graduates will be prepared for high-demand roles in the digital era:
• Digital Humanists & Data Experts: Data-driven analysts for research institutes, NGOs, and international organizations.
• AI Service & Content Strategists: UX researchers and digital service planners for AI education and global communication platforms.
• Tech-Social Policy Analysts: Communication specialists and project managers at global tech firms and diplomatic agencies.
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인문사회과학캠퍼스(서울) 법학관 20208호실 |
| 전화번호 | 02)760-0192 |
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