Ethics of Big Data

Course Description: 

This course provides a forum for discussion on a selection of topics on the ethical and legal aspects of Big Data through mainly contemporary literature in ethics, developments in law, and advances in Big Data technology. We examine case studies on Big Data and then reach conclusions regarding the relevant ethical and legal issues. In examining these case studies, we will also discuss principles and problems of broader philosophical significance. Topics discussed will include the correlation vs causation in data analysis, identity, privacy, and mass surveillance. Principles and problems discussed will include the doctrine of double effect, doing vs. allowing harm, theories of personal identity, and aspects of liberal morality. We will also develop a framework to handle ethical and legal questions in the context of Big Data for individuals, companies and states. No background in ethics or law is required but some affinity to how Big Data is developing is assumed.

Learning Outcomes: 

By the end of the course, students will be able to:

  • demonstrate a clear understanding of debates on central ethical and legal issues in Big Data and be able to take part in these debates by critiquing significant arguments
  • explain how various positions taken on these topics relate to deeper principles and problems in ethics
  • be able to apply a framework of dealing with issues related to Big Data in their workplace
  • perform their own evaluation and critique of the validity and soundness of arguments with care and clarity, both orally and in writing
Assessment: 
  • 20% seminar participation
  • 20% online participation
  • 25% presentation
  • 35% final paper

For further information please check the syllabus.

Prerequisites: 

No background in ethics or law is required but some affinity to how Big Data is developing is assumed.

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