2025 (Current Year) Special graduate degree programs Specially Offered Degree Programs for Graduate Students Center of Data Science and Artificial Intelligence
Progressive Advanced Data Science and Artificial Intelligence 3
- Academic unit or major
- Center of Data Science and Artificial Intelligence
- Instructor(s)
- Kenji Suzuki / Tagui Ichikawa / Asako Kanezaki / Keiji Okumura / Katsumi Nitta / Jun Sakuma / Isao Ono / Yoshihiro Miyake / Takayoshi Yokota / Yutaro Tachibana
- Class Format
- Lecture (HyFlex)
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - 3-4 Wed
- Class
- -
- Course Code
- DSA.A603
- Number of credits
- 100
- Course offered
- 2025
- Offered quarter
- 2Q
- Syllabus updated
- Mar 19, 2025
- Language
- Japanese
Syllabus
Course overview and goals
The rapid evolution of AI improves the convenience of our lives, but it also has social impacts. In this lecture, we teach the ethics of AI in the information society, the information law, and the technologies to realize responsible AI to cultivate a broad perspective beyond the boundaries of the humanities and sciences. This lecture deals with social issues of AI, which were not covered in the course of fundamentals of progressive artificial intelligence.
Course description and aims
The goals are to think independently about ethical, legal, and social issues in today's information society and understand the techniques of explainable AI and fairness.
Student learning outcomes
実務経験と講義内容との関連 (又は実践的教育内容)
・Prof. Tagui Ichikawa has over 30 years of experience in innovation, digital, and AI policy at the Ministry of Economy, Trade and Industry (METI) and related organizations.
・Prof. Kenji Suzuki is engaged in research and development of AI ethics at Sony Group Corporation.
Keywords
AI ethics, Governance, Privacy, Security, Explainable AI, Fairness, Generative AI
Competencies
- Specialist skills
- Intercultural skills
- Communication skills
- Critical thinking skills
- Practical and/or problem-solving skills
Class flow
・Regarding the 2Q class, high-flex classes by face-to-face classes (Ookayama Campus) and Zoom (live) will be held.
・Regarding the 4Q class, Zoom (live) will be held.
Course schedule/Objectives
| Course schedule | Objectives | |
|---|---|---|
| Class 1 | Social Risks and Ethics of AI | Learn social risks caused by use of AI. |
| Class 2 | Data Security and Safety of AI | Learn data security and concept of safety of AI systems. |
| Class 3 | Privacy and Data Protection in the era of AI | Learn privacy issues including that caused by AI. |
| Class 4 | World Trend of AI Regulation and Governance | Discuss on future of AI regulation and governance. |
| Class 5 | Explainable AI | Learn how to interpret black box models. |
| Class 6 | Fairness in machine learning | Learn data bias and fairness in machine learning. |
| Class 7 | Ethical, legal, and social issues of generative AI | Consider various issues in development and use of generative AI. |
Study advice (preparation and review)
In order to improve the effectiveness of the study, students should refer to the relevant sections of the handouts, etc., and spend approximately 100 minutes each for preparation and review (including assignments) of the class contents.
Textbook(s)
None.
Reference books, course materials, etc.
Distributed electronically at T2SCHOLA.
Evaluation methods and criteria
Evaluation is based on in-class assignments, discussion and reports.
Related courses
- XCO.T487 ： Fundamentals of data science
- XCO.T488 ： Exercises in fundamentals of data science
- XCO.T489 ： Fundamentals of artificial intelligence
- XCO.T490 ： Exercises in fundamentals of artificial intelligence
- DSA.A504 ： Advanced Data Science and Artificial Intelligence 4
- DSA.A604 ： Progressive Advanced Data Science and Artificial Intelligence 4
Prerequisites
・Aspiration to increase interest in social issues to learn about ethical aspects of AI.
・Students should have a basic knowledge of machine learning to master responsible AI technologies.
・Guidance will be given in the first class, and students are required to attend the guidance.
Contact information (e-mail and phone) Notice : Please replace from ”[at]” to ”@”(half-width character).
Tagui Ichikawa ichikawa.t.ap[at]m.titech.ac.jp
Kenji Suzuki suzuki.k.ep[at]m.titech.ac.jp
Office hours
Wednesday
Other
・This class is a technical course that can be considered an "Entrepreneurship Course"(GA0D, GA1D).