Summary
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)
- researcher: Marco Favier
- supervisor : prof. Toon Calders
- research is funded by AXA.
- read more on this topic on the website of Antwerp Tax Academy
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
Publications and presentations
Van de Vijver Anne, Calders Toon, be expected Fiscale algoritmen, profilering en het recht op privéleven, Tijdschrift voor Fiscaal Recht, 2020, 611-614 (comment on the Dutch SyRI case)