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The aim of the course is for the student to develop an understanding of the societal implications (risks and opportunities) of increasing data-driven digitalisation, and to be able to communicate knowledge of methods and tools in the field of data science, with relevance for decision-making and sustainable societal development.

The course focuses on how modern data-driven systems give rise to new kinds of ethical dilemmas. The course uses case studies to convey principles and guidelines for managing:

- Data quality
- Data integrity and responsible management of sensitive data (e.g. GDPR, consent)
- Data security (including data ownership, block chain techniques, threats and risk analysis)
- Data-driven and evidence-based decision making
- Neutrality, transparency, reliability, accountability and personal self-determination in a data-driven society.
- Interpretability in machine learning models
- Susceptibility to bias and discrimination as a potential effect of information systems replacing manual processing
- Ethical and sustainability perspectives on data science

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Malmö University provides students who participate in, or who have completed a course, with the opportunity to express their opinions and describe their experiences of the course by completing a course evaluation administered by the University. The University will compile and summarise the results of course evaluations. The University will also inform participants of the results and any decisions relating to measures taken in response to the course evaluations. The results will be made available to the students (HF 1:14).