Transparency, Privacy, and Fairness in Recommender Systems

MediaFutures has invited Dipl.Ing. Dr.techn. Dominik Kowald from Graz, Austria to talk about transparency, privacy and fairness in recommender systems.


6. June.

Time: 12:00 - 13:00


Kowald is research area manager in Fair AI at the Know-Center and senior researcher and lecturer – ISDS (TU Graz). This talk elaborates on aspects related to these three notions in the light of recommender systems, namely: (i) transparency and cognitive models, (ii) privacy and limited preference information, and (iii) fairness and popularity bias in recommender systems.

Recommender systems have become a pervasive part of our daily online experience by analyzing past usage behavior to suggest potential relevant content, e.g., music, movies, or books. Today, recommender systems are one of the most widely used applications of artificial intelligence and machine learning. Therefore, regulations and requirements for trustworthy artificial intelligence, for example, the European AI Act, which includes notions such as transparency, privacy, and fairness are also highly relevant for the design, development, evaluation, and deployment of recommender systems in practice.

Read more about the talk 


Media City Bergen, Læringslab 3rd floor
Lars Hilles gate 30
5008 Bergen


MediaFutures Research Centre