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.
- Within this research objective Marco Favier is doing research on fairness in machine learning. His supervisor is prof. Toon Calders and his research is funded by AXA.
- Ewoenam Topko is working on the same topic of fairness in machine learning. His research is funded by the Flemish government and his supervisor is prof. Toon Calders.
- Also Dahpne Lenders is also working on the same topic of fairness in machine learning, applied on tax data. Her research is funded by the University of Antwerp and her supervisors are prof. Toon Calders en dr. Sylvie De Raedt
Publications and presentations
To be expected