Exactly as humans, artificially intelligent algorithms may generalize in unacceptable ways and unintentionally discriminate certain groups. This sparks a call for deeply embedding ethical rules in data mining algorithms to guarantee fair and unbiased decision procedures. For taxation too, the fairness principle is essential and a major challenge in digitalisation. The main research question here is therefore how to implement ethical considerations in artificial intelligence taxation systems.

Research projects

Fairness in Machine Learning (project 1)

 Fairness in Machine Learning (project 2)

  • researcher: Ewoenam Topko
  • supervisor : prof. Toon Calders 
  • research is funded by the Flemish Government 
  • read more on this topic on the website of Antwerp Tax Academy

Fairness in Machine Learning (project 3) 

  • researcher: Daphne Lenders
  • supervisor : prof. Toon Calders and prof. Sylvie De Raedt
  • research is funded by the University of Antwerp
  • currently working (September - December 2033) on a research project on the use of explainable AI to avoid discrimination in AI models at the Scuola Normale Superiore (Pisa), where she will work with the KDD group ( and under the supervision of prof. Fosca Gianotti (research stay funded by the FWO) 

Publications and presentations