Oudemanhuispoort, Amsterdam, Netherlands

Responsible Data Science in Law & Computer Science (Event 07)

Date: Thursday 16 March

Time: 16:00-17:30

Location: Room A0.08 – Oudemanhuispoort

16:00-16:05 Introduction & Overview on Responsible Data Science by Wil van der Aalst

16:05-16:30 Speaker 1: Linnet Taylor, Assistant Professor, Tilburg Law School

‘What is data justice? The case for connecting digital rights and freedoms on the global level’

Abstract: The increasing availability of ‘data fumes’ – data produced as a byproduct of people’s use of technological devices and services – has both political and practical implications for the way people are seen and treated by the state and by the private sector. Yet the data revolution is so far primarily a technical one: the power of data to sort, categorise and intervene has not yet been explicitly connected to a social justice agenda. In fact, while data-driven discrimination is advancing at exactly the same pace as data processing technologies, awareness and mechanisms for combating it are not. I will argue that just as an idea of justice is needed in order to establish the rule of law, an idea of data justice is necessary to determine ethical paths through a datafying world. I will analyse the existing work on data justice and argue for a framework in which it can be brought together into a single framing for further research and debate.

16:30-16:55 Speaker 2: Joost N. Kok,  Director of the Data Science Research Programme of Leiden University

‘Responsible Monitoring’ 

Numerous entities in cities generate data. All those buildings, infrastructures, production processes and even human relationships can be monitored with the help of data science. This monitoring, in turn, can be the basis for predicting future behaviour of the entities and making decisions about them. We will show a number of our monitoring projects and discuss the responsibility issues.

16:55-17:00 Wrap-up

17:00 – Networking and drinks

17:30 – Close


On 16 March, we will hold our monthly seminar series on Responsible Data Science (RDS), a joint collaboration of expert researchers from 11 knowledge institutions across the Netherlands: Academisch Medisch Centrum (AMC), Centrum Wiskunde en Informatica (CWI), Delft University of Technology (TUD), Eindhoven University of Technology (TU/e), Leiden University (LU), Leiden University Medical Center (LUMC), Radboud University Nijmegen (RU), Tilburg University (UvT), University of Amsterdam (UvA), VU Medical Center Amsterdam (VUmc), VU University Amsterdam.

The RDS initiative is driven by the omnipresence of data making society increasingly dependent on data science. Despite its great potential, there are also many concerns on irresponsible data use. Unfair or biased conclusions, disclosure of private information, and non-transparent data use, may inhibit future data science applications.


The RDS programme aims at generating scientific breakthroughs by making data science responsible by design. In RDS researchers from multiple disciplines connect to develop techniques, tools, and approaches to ensure fairness, accuracy, confidentiality, and transparency.

Big data is changing the way we do business, socialize, conduct research, and govern society. Data are collected on anything, at any time, and in any place. Organizations are investing heavily in Big data technologies and data science has emerged as a new scientific discipline providing techniques, methods, and tools to gain value and insights from new and existing data sets. Data abundance combined with powerful data science techniques has the potential to dramatically improve our lives by enabling new services and products, while improving their efficiency and quality. Many of today’s scientific discoveries (e.g., in health) are fuelled by developments in statistics, data mining, machine learning, databases, and visualization.

For more information see the Responsible Data Science website HERE