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.
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.
✔ Applicable | How instructors' work experience benefits the course |
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・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 Inc. |
AI ethics, Governance, Privacy, Security, Explainable AI, Fairness, Generative AI
✔ Specialist skills | ✔ Intercultural skills | Communication skills | Critical thinking skills | Practical and/or problem-solving skills |
・Face-to-face classes and ZOOM-based high-flex classes will be held.
・Face-to-face classes will be held at Ookayama Campus.
・Attendance at the face-to-face class is recommended for students to actively work on in-class assignments and discussion.
Course schedule | Required learning | |
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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 mitigation methods. |
Class 7 | Ethical, legal, and social issues of generative AI | Consider various issues in development and use of generative AI. |
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.
None.
Distributed electronically at T2SCHOLA.
Evaluation is based on in-class assignments, discussion and reports.
・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.
Tagui Ichikawa ichikawa.t.ap[at]m.titech.ac.jp
Kenji Suzuki suzuki.k.ep[at]m.titech.ac.jp
Wednesday
・This class is a technical course that can be considered an "Entrepreneurship Course"(GA0D, GA1D).