Aims

Digital technologies are ever more pervasive in everyday life and in our social institutions, resulting in characterizations of contemporary European societies as ‘Digital’, ‘Data-driven’, or ‘Smart’. This course presents an advanced introduction of digitalisation in, and of, European societies. First, it offers critical, theoretical and analytical tools into the social dimensions and implications of developments in the domain of datafication, digitalisation, and automation. The aim is to acquaint students with core social science perspectives on Big Data, drawing from Science and Technology Studies (STS), critical data studies, and governance of data literature. Secondly, the theoretical background will be employed to analyse relevant topics and cases on the ethical, legal and social challenges of digitalisation, in societal domains such as health care, insurance, social policy, work, and the welfare state.

Upon completion of this course the students have reached the following objectives:

• Students know core social science perspectives and approaches in order to reflect, discuss and address the societal dimensions and challenges resulting from developments in the domain of digitalisation in European societies.
• Students can illuminate the wide range of societal challenges resulting from developments in the domain of digitalisation with empirical cases and examples from critical data studies, Science and Technology Studies (STS), and governance of data literature.
• Students are equipped with the analytic and conceptual skills necessary for a critical and productive engagement with literature in the social sciences at the interface of big data and society.

These objectives are announced at the start of the course.

Previous knowledge

At the beginning of the course, students are supposed to be interested in the social reality, its problems, prevailing values and standards, particularly with regards to emerging and established data practices. Students can critically approach conceptual frames, have the appropriate academic skills to write a paper, reason, abstract, discuss and communicate. No prior technical knowledge of data science and/or digital innovations is required for this course.

Is included in these courses of study

• Master in de sociologie (Leuven) 60 ects.
• Master in het sociaal werk en sociaal beleid (Leuven e.a.) 60 ects.
• Courses for Exchange Students Faculty of Social Sciences (Leuven)
• Master of Sociology (Leuven) (Quantitative Analysis and Social Data Science (QASS)) 60 ects.
• Master of Sociology (Leuven) (Solidarity and Social Risks in Europe) 60 ects.