Abstract:

Ethics is everywhere. We need to get our research plans approved by ethics boards, we now do ethical AI (based on ethics codes), the European Union makes data-science projects have an independent ethics advisor, and management now engages in ethical leadership.
    Why is this, and what does ethics actually mean in the context of data science? In this talk, I will give a hands-on introduction to important schools of thought and questions from this fascinating subfield of philosophy. The “hands-on” means that we will, interactively, go through a number of real-life case studies from data science, study what values and rights are at stake and how they were and can be disregarded, respected, protected, and questioned.   
    In the second part of the talk, I will focus on a specific application of ethical questioning: the analysis of vehicle/human trajectory data, and a specific value: privacy. I will discuss two recent examples of the analysis of such data – the New York City taxi rides dataset, and the use of data from the maritime Automatic Information System (AIS) for mapping refugee movements on the Mediterranean Sea. The examples will illustrate a feature that engineers often find very difficult to deal with: the tension between allowing for different (and often mutually incompatible) ethical stances on the one hand, and requiring adherence to certain ethical norms that are considered non-negotiable on the other hand. But these examples will also illustrate why we should care, why it is intellectually stimulating to think about ethics, and why doing so requires us to also question ethics or “ethical” codes, boards and advisors, and certainly leaders. 

Brief Bio:

Bettina Berendt is a professor in the Artificial Intelligence / Machine Learning and Data Mining group at the Department of Computer Science at the University of Leuven. Her research interests are data and text mining and in particular the interactions with how people make decisions faced with the artificial and human intelligence they find online. This means investigating how mining affects and interacts with privacy and data protection, how it can liberate and increase diversity – or discriminate, and what ethical choices people face when dealing with data and data science. Within this range of topics and methods, Bettina has concentrated on combining methods from data mining, HCI, and behavioural economics, and investigated questions arising for data subjects, researchers, institutional decision-makers, teachers, and regulators.

Before coming to Leuven, Bettina studied Business, Economics, and Artificial Intelligence in Berlin/Germany, Cambridge/UK and Edinburgh/UK. She obtained her PhD in Computer Science and Cognitive Science from Hamburg University/Germany and her Habilitation in Information Systems from Humboldt University Berlin.

Host:  Stan Matwin (stan@cs.dal.ca)