Stirred and shaken - interdisciplinary social science

Data governance

Stirred and shaken - interdisciplinary social science

Data governance

Summer 2019 - new version from Fall 2020 as part of the Social Data Science M.Sc. program.

Main lecturer: Kristoffer Albris.

Co-lecturers: David Dreyer Lassen and Morten Axel Pedersen.

Link to UCPH page on course details

The age of social big data brings with it a range of ethical, legal and political issues. From the ethics of protecting individual online privacy, to the legal frameworks regulating internet giants such as Facebook and Google, new data governance issues surface at a rapid pace. This course provides students with an introduction to key legislative, political and ethical principles and debates from the perspectives of anthropology, law, sociology, political science, and related disciplines, concerning the governance of data, needed for a range of analysis and management positions across private, public and non-profit organizations.

Data governance concerns the overall management of the availability, usability, integrity and security of data used in private, public and non-profit organizations. Comprehensive data governance addresses issues of data stewardship, ownership, compliance, privacy, data risks, data sensitivity and data sharing, including how such issues exist between different entities within the same organization. It involves thinking through issues such as: What do new forms of data-driven surveillance mean for relations between citizens, businesses and nation states, and how are new legal issues such as the legal basis for decision support systems and algorithmic decisions in public and private organizations addressed within current European legislation? Students will be taught how to develop and implement ethically and politically informed procedures and infrastructures for organizing, managing and maintaining data and data products in public and private organizations. The course also introduces the most recent ethical and social-scientific models of data governance, including organizational models and risk assessments, and asks students to apply them to a real-world case of problem solving.

Casework takes students through the main phases of data governance analysis and practice: identification of a data-related problem and its internal and external stakeholders; analysis of how legal, technical-infrastructural and social-organizational components of the problem interrelate; pre-screening of possible solutions, including their respective risks; and final proposal and pilot check of a new data governance scheme expected to be robust in the face of foreseeable near- and mid-term challenges. By drawing on cutting-edge research in anthropology, law, sociology, and related disciplines, the students will also be able to contextualize and situate the case-based work within existing scientific debates concerning data governance and ethics. The course is organized into three parts. First, we begin with an introduction to what can be done with social big data under current Danish and EU laws. This is followed by a consideration and discussion of what should (and should not) be done in more political and ethical terms. And finally, the course will discuss what could be done in terms of governance in different sectors of public administration (health, education, etc.), in the private business sector and in the non-profit sector.

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David Dreyer Lassen
Prorector
Research and Innovation
&
Professor of Economics