Academic expert training 2023
Target audience:
- Tax professionals;
- Tax authorities (including tax data miners);
- Tax accountants;
- Tax consultancy;
- Corporate lawyers;

Two-day program (one day Amsterdam, one day Antwerp), participants can follow both days or only one. Vrije Universiteit Amsterdam will emphasize collecting (big) data, and Universiteit Antwerpen will focus on analyzing.

Click here to find the brochure (pdf)

Register here

Day I – Friday January 27th 2023

Vrije Universiteit Amsterdam



Saturday January 28th 2023


13.00- 17.00 Social programme in Amsterdam

Guided tour in Rijksmuseum and drinks
Our tour will be a presentation of the Rijksmuseum collection is a journey through Dutch art and history from the Middle Ages and Renaissance until the 20th century. For the very first time, visitors can follow a chronological journey through the collection, and experience the sense o beauty and time this offers. The story of the Netherlands has been set in an international context and is told chronologically across four separate floors. A surprise guided tour that will paint a beautiful picture of the kind of things the Rijksmuseum has to offer. From Rembrandt's Night Watch to a 20th-century plane, from extravagant pieces to a complete, original 18th-century period room. After the tour, we will head for drinks and snacks to the one of the brown cafes for a taste of authentic Amsterdam flavour and Dutch culture. Brown cafes (in Dutch bruin café) are a quintessential part of Amsterdam’s culture.

Cost: 80 euro

Sunday January 29th 2023


We invite you to visit the KMSKA, the Royal Museum of Fine Arts of Antwerp. After 11 years, the museum is reopening its doors. The building underwent a complete metamorphosis. (Re)discover the building and especially the rich collection of artworks under the guidance of a guide, together with other participants of the Tax and Technology Expert Training.

Afterwards, we offer a drink in the cozy bar of the KMSKA.

2 - 4 p.m.: guided tour of the KMSKA
4 - 5 p.m.: closing drink.

We gather at 1:45 p.m. at the reception desk, ground floor of the mused Leopold de Waelplaats 1, 2000 Antwerp

EUR 50. This price includes the visit to the museum and the closing drink.

Day II - Monday January 30th 2023

Universiteit Antwerpen


•   9.00: Welcome – prof. dr. Sylvie De Raedt, tax law professor and research manager DigiTax UAntwerp

•   9.05: A functional taxonomy of AI fiscal governance in the EU (David Hadwick, PhD candidate in tax law at DigiTax Uantwerp & PhD Fellow at the FWO - Research Foundation for Flanders)
In two decades, the proliferation of use of AI by tax administrations has been nothing short of outstanding from a handful of Member States in the early 2000s to a majority of EU tax administrations making daily use of the technology. This presentation will outline the current state of use AI by tax administrations in the EU, the Member States that make use of AI, the types of AI models used and the different functions performed.

•   9.50 The legal limits of webscraping (prof. dr. Sylvie De Raedt)
This part of the program will discuss the automated collection of data through webscraping, and will explore the relevant case law of the European Court of Human Rights as well as the GDPR requirements to define the legal limits of webscraping. How does the practice of webscraping relate to the prohibition of fishing expeditions? What are good practices?  

•   10.35: Coffee break

•   10.50: Getting ready for data analysis: what about data quality (Michiel Van Roy, PhD Candidate in Applied Economics, Faculty of Business and Economics and Digitax UAntwerp)
The reliability of predictive machine learning models can be compromised when trained on low quality data. Algorithms that can automatically identify low quality data in datasets are highly desired. This session will explore one of such algorithms, based on the Shapley value, along with its challenges and limitations.

•   11.30: Predictive algorithms for fraud detection (Daphne Lenders, PhD candidate in Computer Science, Adrem Data Lab and DigiTax UAntwerp)
One of the many application areas of Artificial Intelligence are predictive algorithms, which can automate decision processes, normally made by humans. After providing a general introduction about such algorithms, we will explore through a case study their potential for detecting tax fraud from data. What benefits can these algorithms bring? And perhaps more importantly: what challenges and risks do they give rise to?  

•   12.30: Networking lunch at the faculty club


•   14.00: Algorithmic bias and automation bias: the legal perspective (prof. dr. Anne Van de Vijver, tax law professor DigiTax UAntwerp)
Algorithmic bias refers to automated decisions that are systematically unfair to certain groups of people, while automation bias is the propensity of people to prefer suggestions from automated decision-making systems and to ignore contradictory information. This session will explore how the legal system sets limits to discriminatory biases. How do fundamental rights protect taxpayers from biased decision-making?

•   14.30: Methods to measure bias and mitigate unfairness when constructing machine learning models (prof. Toon Calders, professor in computer science)
Artificial intelligence is more and more responsible for decisions that have a huge impact on our lives. But predictions, made using data mining and algorithms, can affect population subgroups differently. Academic researchers and journalists have shown that decisions taken by predictive algorithms sometimes lead to biased outcomes, reproducing inequalities already present in society. In this presentation we will present an overview of recent research on measuring bias in data and how to avoid such bias to result in unfair models.

•   15.20: Break

•   15.30: Data analysis and automated decision making: transparency requirements (prof. dr. Sylvie De Raedt and David Hadwick)
Data collection and automated decision-making systems have now become an integral part of our daily lives. This type of innovation also seems to have brought new risks - risks to fundamental rights, distrust and disruptions of institutional processes. In the context of automation, transparency has been hailed as the new keyword. Yet, transparency is an elusive concept spanning across different areas of the law. This presentation will showcase the different transparency requirements, in ECtHR jurisprudence, the GDPR and the Proposal for the AI Act.

•   16.20: How to explain the black box decision (Dieter Brughmans, PhD candidate in Data Science at Digitax Uantwerp)
Businesses are increasingly turning to machine learning systems to automate and enhance their operations and decision-making. By making use of complex modeling techniques, they are able to create models with high and sometimes superhuman predictive performance. However, given their complexity, these models are often used as black-boxes for which it is unclear how predictions are made. This has led to the development of a new field called eXplainable Artificial Intelligence (XAI) which studies how these algorithms can be made comprehensible for humans again. In this presentation, we will discuss how different XAI algorithms can be used to explain black-box predictive models.

•   17.00: Closing drink

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