The name "Tsing-Hua" (清华) comes from the Chinese phrase "水木清华" (shuǐ mù qīng huá), which originates from a line in a classical Chinese poem: "水木湛清华" (the water and trees are lush and beautiful). The name symbolizes elegance, purity, and scholarly pursuit.
Tsinghua University (Beijing, China)
National Tsing Hua University (Taiwan)
Do They Share the Same Mission/Slogan?
Yes, both universities use the exact same motto (自強不息，厚德載物), reflecting their shared heritage before the Chinese Civil War (1949).
However, their governance, funding, and political affiliations differ due to the cross-strait divide.
Key Differences
| Aspect | Tsinghua University (Beijing) | National Tsing Hua University (Taiwan) |
|---|
| Founded | 1911 (Beijing) | 1956 (Hsinchu, Taiwan) |
| Affiliation | PRC (Ministry of Education) | ROC (Taiwan's Ministry of Education) |
| Global Ranking | Top in China (QS/THE) | Top in Taiwan (QS/THE) |
| Focus | Strong in STEM, policy influence | Strong in semiconductors, tech research |
Conclusion
Both universities share the same name origin and motto, stemming from their common history. However, they operate under different political systems today, leading to distinct academic and research directions.
Would you like more details on their academic strengths or historical ties?
AI overview syllabus 2025
SyllabusArtificial Intelligence and Policy Tools人工智慧與政策工具Spring 2025
PROFESSOR H.T. KUNG & JIUNN-RONG YEH
孔祥重, 葉俊榮
TAIPEI SCHOOL OF ECONOMICS AND POLITICAL SCIENCE,
NATIONAL TSING-HUA UNIVERSITY
I. INTRODUCTION
The development of artificial intelligence (AI) grows rapidly, making profound
impacts on people’s welfare and governmental operations. However, policies and laws
concerning AI regulation has still presented a mismatch with its technological
potentials. This course “Artificial Intelligence and Policy Tools” is directed primarily
to training decision-making professionals working at the intersection of technology and
policy in preparation for the emerging era of ubiquitous AI. Issues concerned in the
course includes why and how to regulate AI form national and global perspectives.
Regulatory Modles developed or in developing will be assessed in its merits and
deliberative process, with a focus on the development of policy tools in public
governance and private domain as well.
This course will involve relevant literature and project for presentation and
discussions. Both the instructor and students are all expected to embrace these materials
and to engage in dialectical learning. At the end of the semester, students are required
to submit a project report with ideas inspired or developed during the class.
II.
COURSE GOAL
1.To train decision-making professionals working at the intersection of technology
and policy in preparation for the emerging era of ubiquitous AI
2. To formulate a general analytic framework for AI policy and regulation in
preparation for the emerging era of ubiquitous AI
III. COURSE SCHEDULE
The Course is divided in two parts, instructed by Professor Yeh for the first part
and and Professor Kung for the second part. The first part, weeks1-7, on policy and
regulation, aims at a general understanding of AI policy formation and regulatory
2
framework. The second part, Week 8-11, technology and system, is directed to a
working comprehension of AI technology system and policy tools.
2/19 Week 1 AI Technology, Policy, Law and Regulation
Prof. Jiunn-rong Yeh
Progress and Regulation, Technology Policy and Institutions, Regulating Technology,
AI Legislation: Basic Law and Others, EU Artificial Intellegence Act, AI in
Technology, Information, Data and Speech
# Žiga Turk, Regulating Artificial Intelligence: A Technology-Independent Approach,
23 EUROPEAN VIEW 87 (2024).
# Dmitryi L. Kuteynikov & Osman A. Izhaev, Analysing Risk-Based Approach in the
Draft EU Artificial Intelligence Act, 4 LEGAL ISSUES DIGIT. AGE 97 (2023).
2/26 Week 2 Regulatory Goal and Deliberation: Progress and Externalities
Prof. Jiunn-rong Yeh
AI: Benefit and Risk, Red-light v. Green-light Rules, AI and National
Competitiveness, Ai Souvereignty, AI Toxics, Black Box, and Discrimination,
Externalities and Human Rights, Privacy, Transparency and Stakeholder
Participation.
# Keri Grieman & Joseph Early, A Risk-Based Approach to AI Regulation: System
Categorisation and Explainable AI Practices, 20 SCRIPTED 56 (2023).
# Isabel Kusche, Possible Harms of Artificial Intelligence and the EU AI Act:
Fundamental Rights and Risk, JOURNAL OF RISK RESEARCH 1 (2024).
3/12 Week 3 AI Regulatory Regime: Goal and Tools
Prof. Jiunn-rong Yeh
Risk-based Regulation, Risk and Categorization, Property Rights, Permitting,
Standard-setting, Economic Incentives, Sand box
# Jyh-An Lee, Algorithmic bias and the New Chicago School, 14 LAW INNOVATION &
TECH. 95 (2022).
# Miriam Buiten etc., The Law and Economics of AI Liability, 48 COMPUTER LAW &
SECURITY REVIEW (2023).
3/19 Week 4 AI Regulation: Public and Private Domains
Prof. Jiunn-rong Yeh
3
Corporate Responsibility, Command and Control, Market Mechanism, Incorporation
of Private Rules, AI Sovereignty, AI Deliberation, Autonomy and Humanity, AI and
Global Order
# Daniel Mügge, EU AI Sovereignty: For Whom, to What end, and to Whose Benefit?,
31 JOURNAL OF EUROPEAN PUBLIC POLICY 2200 (2024).
# Martin Petrin, AI, New Technologies, and Corporate Governance: Three Phenomena,
47 SEATTLE U. L. REV. 1639 (2024).
4/16 Week 5 AI: Impact Assessment
Prof. Jiunn-rong Yeh
AI in Government Functions, FDA New Drug Review, Job Displacement, Legitimacy
and Liberty, Accountability and Integrity
# Andrew D. Selbst, An Institutional View of Algorithmic Impact Assessments, 35
HARV. J. L. & TECH. 117 (2021)
# Claudio Novelli etc., Accountability in Artificial Intelligence: What It is and How It
Works, 39 AI & SOCIETY 1871 (2023).
4/23 Week 6 AI: Finance and Liability
Prof. Jiunn-rong Yeh
Tax or Fees, AI Insurance, Property Rule, Liability Rule and Rule of Inalienability,
Causation, Injury in Fact, AI Fund
# Anat Lior, Insuring AI: The Role of Insurance in Artificial Intelligence Regulation,
35 HARV. J. L. & TECH. 467 (2022).
# Beatriz B. Arcila, AI Liability in Europe: How Does it Complement Risk Regulation
and Deal with the Problem of Human Oversight? 54 COMPUTER LAW & SECURITY
REVIEW (2024).
4/30 Week 7 AI in Global Regulatory Order
Prof. Jiunn-rong Yeh
Models of Regulation, Regulating International Transfer of Technology, Global AI
Networking, Global Administrative Law, Mega Regulation, International Trade,
Health, and Environmental Regulation
# Scott J. Shackelford & Rachel Dockery, Governing AI, 30 CORNELL J. L. & PUB.
POL'Y 279 (2020).
4
# Yoshija Walter, Managing the Race to the Moon: Global Policy and Governance in
Artificial Intelligence Regulation—A Contemporary Overview and an Analysis of
Socioeconomic Consequences, 4 DISCOVER ARTIFICIAL INTELLIGENCE 14 (2024).
5/9 Week 8 AI Technology
Prof. H. T. Kung
Pre-Trained AI Models for Computer Vision and Natural Language Processing,
Model Alignment, Fine-Tuning, Prompt Engineering, Industrial Applications, Risks in
Using AI, Societal Impacts, AI Sovereignty, and National Competitions
5/16 Week 9 AI Systems
Prof. H. T. Kung
AI Training and Inference, Data Curation, AI Chip Development, Taxonomy and
Benchmark Development in Model Localization, System Deployment, open-Source
Approaches, and Safety
5/23 Week 10 Policy Tools
Prof. H. T. Kung
AI Resource Sharing, Talent Nurturing, Energy Provisioning, Education Adaptation,
International Trading of Model and Data Asset, AI Safety, Model Security, Data
Privacy, Technology Decoupling, and Resilient Supply Chains
6/4 Week 11 Presentation and Discussion
Prof. H. T. Kung
Final Project Presentations and Report Discussions
Course Projects
Via course projects, students develop short position papers on novel ideas at the
intersection of technology and policy to address national challenges. Below are
example project topics:
-
Trade and technology policies on Taiwan's import/export of AI foundation models
- Data policies for supporting AI model localization and alignment
-
Modifying traditional trade policy levers for AI model and data assets
-
Energy policy in accommodating large-scale inference requests from humans and
devices
- Sharing of human and computing resources in model training and fine-tuning
-
Enhancing security and privacy in remote AI inference
-
Taxonomies characterizing Taiwan's democratic values and the associated
5
benchmark development
- Incentives for investing in validating functionalities and security of AI models
and their continuous upgrading
-
Resilient AI supply chains under geopolitical uncertainties
-
Education policy on the use of Chat GPT in grade schools
-
Strategies for mitigating AI-induced digital divides
- Comparative analysis for an archetypal set of nations such as Taiwan, US, China,
Japan, South Korea, and India
