Home

Welcome to the home page of the Ghent University 2019 Summer School for Trust in Data Science to be held 19-21 June 2019 at Ghent, Belgium!

The increasingly central role of data in today’s economy, as well as in data-driven research (e.g. the digital humanities, medicine, biology), has brought to the fore important questions around data ownership, data protection, privacy, and fairness of data-driven algorithms. This course covers the technical and legal aspects of how to ensure data science approaches can be trusted to treat individuals fairly and with consideration for privacy. Trust is achieved when ethical practices in data science are followed.

This is a specialist course organized in the context of the UGent doctoral schools of Engineering and Natural Sciences. This course will be of interest to researchers into data science algorithm design as well as to researchers working with personal data; the target group will include computer scientists, electrical and biomedical engineers, bioinformaticians, neuroinformaticions, medical informaticians, statisticians, molecular biologists, and other researchers and developers.The summer school will be open to graduate students, PhD students, postdoctoral researchers and early-career professionals in any field related to data science.

Data science is a field that is rapidly growing in importance due to a rapid growth of available data, computing power, and recent algorithmic developments. This poses obvious risks to the privacy of the data subjects, and to data protection more generally. However, it also entails two complementary opportunities. First, it may result in more effective decisions based on e.g. advanced machine learning techniques. Second, it makes it possible to also formalize ethical constraints regarding e.g. fairness and (paradoxically) also privacy, which can then be enforced on those data-driven decisions. Both of these opportunities are intimately tied to the increased accessibility of data, and are undeniably beneficial. For example, today judges still make their verdicts based on a combination of the facts, a subset of the law and jurisdiction, and (often unconsciously) personal biases. Doctors still make decisions based on their (limited) expert knowledge, the symptoms, combined with personal intuition. The increased availability of data well beyond personal anecdotal experience can not only reveal the existence of personal biases or intuition, it can also ensure the decisions are in accordance with ethical and legal constraints, while also improving those decisions in making them more evidence-based.

Formalizing ethical and legal constraints is however non-trivial, and research has only recently started to substantially invest in these questions. Yet, providing a constructive answer to these questions is a prerequisite for data science approaches to deserve the trust of its users. This specialist course should be of interest to anyone performing or using data science research broadly defined.

For any question regarding the course, please send us an email to TDS [at] ugent.be or visit the registration page. Registration deadline is June 13!