SIKS-course “Explainable AI”


On the Tuesday and Wednesday afternoons of September 21-22 and 27-28, 2021, the School for Information and Knowledge Systems (SIKS) organizes the new course on “Explainable AI” in cooperation with the Hybrid Intelligence Centre. This two-day course will be divided over four afternoons. The course will be given in English and is part of the Educational Program for SIKS-PhD-students. It is a course with a broad focus, aimed at all SIKS-PhD-students regardless the research area they are actually working on. Although this course is primarily intended for SIKS-PhD-students, other participants are not excluded. However, their admittance will be restricted and depends on the number of SIKS-PhD-students that wish to enroll.

In politics, industry and science, much attention is paid today to the ethical and social aspects of AI, the risks of big data and the increasing power of incomprehensible and opaque algorithms, which are seemingly objective, “value-free” and neutral, but which make radical decisions without human intervention, that may deeply influence people and their future. The call for Explainable AI therefore sounds louder all the time. Many researchers who participate in SIKS are directly or indirectly involved in this issue, often in various ways and from different perspectives. All this makes a solid place of Explainable AI in the SIKS Activity Program imperative.

We recommend that PhD students considering taking part in this course carefully read the following paper as a general introduction to the topic: Miller, T., 2019. Explanation in artificial intelligence: Insights from the social sciences. Artificial Intelligence, 267, pp.1-38.

21 September 2021, 13.00-17.00 hrs
22 September 2021, 13.00-17.00 hrs
28 September 2021, 13.00-17.00 hrs
29 September 2021, 13.00-17.00 hrs

Prof. dr. Rineke Verbrugge (RUG)
Dr. Afra Alishahi (TiU)


September 21
13:00-13:15 Rineke and Richard: General Introduction, structure of the program, speakers, etc.
13:30-15:00 Maarten de Rijke: Introduction
15:30-17:00 Emily Sullivan: Ethical challenges of Explainable AI

September 22
13:00-14:00 Zeynep Akata: Natural Language Explanations for Visual Classification Decisions
14:15-15:45 Chris Emmery: Explainability and digital privacy
16:00-17:00 Bart Verheij: Explainable AI and Law

September 28
13:00-14:15 Jelle Zuidema: Interpretability and bias detection in neural language models
14:30-15:45 Frank Dignum: The social origin of explainable AI
16:00-17:00 Ilaria Tiddi: Explanation generation for intelligent systems

September 29
13:00-14:15 Kerstin Bunte: Interpretable machine learning for interdisciplinary data science
14:30-15:30 Student Presentations
15:50-16:50 Student Presentations
16:50-17:00 Closing remarks


Registration is closed.