Official course description:
Full info last published 15/11-19

Data: Law and Ethics

Course info
Language:
English
ECTS points:
7.5
Course code:
BBDALAE1KU
Participants max:
50
Offered to guest students:
yes
Offered to exchange students:
Offered as a single subject:
yes
Price (single subject):
10625 DKK (incl. vat)
Programme
Level:
Bachelor
Programme:
BSc in Global Business Informatics
Staff
Course manager
Assistant Professor
Teacher
Part-time Lecturer
Teaching Assistant
Assistant Lecturer
Teaching Assistant
Assistant Lecturer
Course semester
Semester
Forår 2020
Start
27 January 2020
End
31 August 2020
Exam
Exam type
ordinær
Internal/External
intern censur
Grade Scale
7-trinsskala
Exam Language
GB
Abstract
This course examines the socio-political, ethical and legal contexts of data by investigating a range of recent data controversies. In this course students will learn to critically reflect upon the multiple ways data is articulated as a controversial legal and ethical object.
Description

Our contemporary moment is increasingly characterized by and through data. Data is said to be the new oil or currency, perhaps even a new vehicle of societal growth. From quantified-self movements to new forms of economics (such as bitcoin and platform capitalism) and sensing-based environments (the internet of things), data continues to proliferate and multiply. In this process, data is transforming people, organizations and societies. This ‘data moment’ poses important empirical, theoretical, legal and ethical challenges. It is an opportunity to take stock of how we might engage and think with data.

This course will examine the historical, socio-technical, political, ethical and legal contexts of data. In highlighting the various modes and forms through which data emerges, the course will encourage students to engage both critically and reflexively with how data is generated, circulated, stored, analyzed and consumed. We will guide students in this endeavor by adopting a social scientific approach, focused on analyzing, interpreting and understanding the meaning of contemporary data practices in organizations, society and government. At the same time, the course will also feature legal and ethical perspectives on data and data protection, focusing on the General Data Protection Regulation (GDPR) and similar legislation and its oversight. This will equip students to connect contemporary legal and ethical concerns with wider political and technical contexts. Taken together, the course will push students to ask: Who has the right to use and own data? How and for what purposes should data be used? Who benefits from the intensified use of data and who gets left out? What are the economic incentives for using data? And what does it mean to work with data in legally acceptable and ethically responsible ways?

Formal prerequisites

There are no formal prerequisites for being admitted to the course.

Intended learning outcomes

After the course, the student should be able to:

  • Describe the ways in which data is conceptualized within the course literature
  • Situate and contextualize data in its historical, ethical, technical, legal and political contexts
  • Develop a case study that focuses on a contemporary data controversy/concern
  • Analyze and examine the data practices involved in this case study
  • Use this case study to reflect upon and critically discuss the ethical and legal dimensions of data
Learning activities

The course consists of lectures and exercises. The lectures will primarily focus on presenting and discussing various social scientific approaches to data. During the exercises you will work in groups on the themes brought up in the lecture. Here you will carry out small case studies, train your analytical skills and your ability to collaborate, as well as give oral presentations and constructive feedback.

Course literature

The course literature is published in the course page in LearnIT.

Student Activity Budget
Estimated distribution of learning activities for the typical student
  • Preparation for lectures and exercises: 30%
  • Lectures: 20%
  • Exercises: 25%
  • Project work, supervision included: 10%
  • Exam with preparation: 15%
Ordinary exam
Exam type:
C: Submission of written work, internal (7-trinsskala)
Exam variation:
CG: Submission of written work for groups.
Exam description:
T

reexam
Exam type:

Exam variation: