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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.

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
• 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) 

2023

• Tokpo Ewoenam Kwaku, Delobelle Pieter, Berendt Bettina, Calders Toon, , Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2023), May 2-6, Dubrovnik, Croatia - Association for Computational Linguistics, 2023, p. 3418-3433
  
• Lenders Daphne, Calders Toon, , AI Ethics, 2023
  
• Lenders Daphne, Calders Toon, , HHAI 2023: Augmenting human intellect: Proceedings of the Second International Conference on Hybrid-Artificial Intelligence / Lukowicz, Paul, p. 426-428
  
• Lenders Daphne, Calders Toon, , Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing (SAC '23), March 27 – March 31, 2023, Tallinn, Estonia, p. 350-357
  
• Pinxtere Sam, Favier Marco, Calders Toon, , Machine learning and principles and practice of knowledge discovery in databases, ECML PKDD 2022, PTI - European Conference on Machine Learning and Principles and Practice of, Knowledge Discovery in Databases (ECML PKDD), SEP 19-23, 2022, Grenoble, France, Cham :Springer international publishing ag, 2023, p. 336-352
  

2022

• Tokpo Ewoenam Kwaku, Calders Toon, , ​NAACL 2022: The 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: proceedings of the student workshop, Human Language Technologies, JUL 10-15, 2022, Seattle, WA - Stroudsburg :Assoc computational linguistics-acl, 2022, p. 163-171
  
• Goethals Sofie, Martens David, Calders Toon, , Research Square, 2022, 31 ss.
  

2021​

• Lenders Daphne en Calders Toon, , 21st Joint European Conference on Machine Learning and Principles and, Practice of Knowledge Discovery in Databases (ECML PKDD), SEP 13-17, 2021, Cham : Springer international publishing ag , 2021, 631-646

• Pieter Delobelle, Ewoenam Kwaku Tokpo, Toon Calders, Bettina Berendt:, Measuring Fairness with Biased Rulers: A Survey on Quantifying Biases in Pretrained Language Models. CoRR abs/2112.07447 (2021)

• Pinxteren Sam, Calders Toon, , 2021 SIAM International Conference on Data Mining (SDM), 2021, p. 9-27 

• Calders Toon, Ntoutsi Eirini, Pechenizkiy Mykola, Rosenhahn Bodo, Ruggieri Salvatore, , SIGKDD explorations 2021, p. 1-3

2020

• Van de Vijver, Anne, Calders, Toon, , Tijdschrift voor Fiscaal Recht, 2020, 611-614 (comment on the ) ​