The course is a postgraduate series of seminars addressing selected topics of artificial intelligence. The course is structured into two branches. The AI Robolab is responsible for Branch II: AI Ethics and Explainability.
AI Ethics and Explainability
With the widespread use of sophisticated AI applications,researchers started to study the underlying ethical principles guiding these systems. Furthermore, this tendency has been encouraged by recent calls, white papers, and guidance documents stressing the importance of AI Ethics and AI Transparency. In this first part, this course gives an overview of recent research works addressing AI Ethics, their applications, and their implementation in robots and multi-agent systems. In the second part, the course focuses on introducing eXplainable AI (XAI) and presenting its applications in machine learning (interpretable ML and DNNs, LIME, etc.) and explainable agents and robots.
The course supervisor defines a list of research articles. Each lecture, a research article is presented by a student followed by a discussion animated by the course supervisor and questions asked by other student participants.
In addition to introducing the students to this recent topic, the course aims to make students familiar with research methodology and help them get used to reading scientific articles, identifying their contributions, limitations, positioning them vis-à-vis other related research works, and highlight the future research perspectives
List of lectures
Overview of the course content and structure, presentation of further topics.
Reading task for students in the branch "AI Ethics":
- An Introduction to Ethics in Robotics and AI (Bartneck, Lütge, Wagner, Welsh) Chapter 3 (p. 17-26)
- The Nature, Importance, and Difficulty of Machine Ethics (Moor) (p. 1-4)
Title : Explainable agents and robots: Results from a systematic literature review (Anjomshoae, Najjar, Calvaresi, Framling) AND Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI) (Adadi & Berrada)"
Name of student : HO HaoCheng
Teacher : Amro Najjar
Date : November 24,2020
+ Explainable agents and robots: Results from a systematic literature review (Anjomshoae, Najjar, Calvaresi, Framling) AND Peeking Inside the Black-Box: A Survey on
+Peeking Inside the Black-Box- A Survey on Explainable Artificial Intelligence (XAI) (Adadi & Berrada)