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Overview
The course "Fairness in Artificial Intelligence” addresses social problems at the interface of artificial intelligence, fair division, economy and computer science. The main goal of this course is to give to students the opportunity to work on state-of-the-art research projects that integrate fairness concepts in various fields of AI.
Learning Goals and Syllabus
Goals:
The aim of this course is to train students on basic research skills that are often not in the prime focus of a regular university course. On successful completion of the course, students will be able to
- develop mathematical models (with real-world features),
- describe and design (efficient) algorithms,
- write a scientific report/paper,
- analyze properties of algorithms (e.g. complexity, characterizations, etc.),
- develop their critical thinking,
- learn to share the workload and responsibility, and
- work in (research) teams.
Syllabus:
Please click here for the course syllabus.
You may find the syllabus useful when discussing with your home University whether the ECTS credits attainable for this course are accepted by them.
Prerequisites
There are several obligatory and preferable requirements for this course:
- Obligatory: At least one year of university experience.
- Obligatory: English level B2 or equivalent.
- Obligatory knowledge: Algorithms, Mathematics.
- Obligatory skills: Programming in C, C++, Java, Perl or Python.
- Preferable knowledge: Economics, Computational Complexity.
- Preferable skills: LaTeX (a typesetting system).
Lecturers
Martin Aleksandrov obtained a Bachelor degree in Computer Science from Sofia University, Bulgaria. He also received a Master degree in Computer Science from Technical University of Dresden, Germany. In addition, Martin obtained qualifications as Bachelor in Physics and Master in Probability Theory and Statistics from Sofia University, Bulgaria.
Martin received his PhD in Computer Science from UNSW Sydney, Australia. He was an intern at Fondazione Bruno-Kessler (FBK in Trento, Italy) and Australian ICT Research Centre of Excellence (fka NICTA in Sydney, Australia). He also worked at NOVALINCS (fka CENTRIA in Lisbon, Portugal).
He won the Computational Sustainability Outstanding Student Paper Award at 24th IJCAI 2015, Buenos Aires, Argentina, and the Best Paper Award at 40th KI 2017, Dortmund, Germany.
Please direct questions about the course to the TU Berlin Summer University Team at: summeruniversity(at)tubs.de. We will answer your questions and direct specific queries regarding course content to the course lecturers where necessary.
