620088 :Data Science: Sustainability, Privacy and Security

Algemeen

Voertaal Engels
Werkvorm: Interactive lectures and guest lectures. (Collegerooster)
Tentamenvorm: 1. Class participation (graded pass/fail), composed of required attendance of 80% per cent of the course, and in-class knowledge test (form described in the course syllabus). A ‘pass’ for class participation is required for admission to the written exam. 2. 3 paper assignments – total of 30% of the final grade; 3. Written exam – 70% of the final grade. (Tentamenrooster)
Niveau:Master
Studielast:6 ECTS credits
Inschrijving:
Blackboard informatieLink to Blackboard (Als u de melding 'Guest are not allowed in this course' krijgt, dient u nog bij Blackboard in te loggen)

Docent(en)


dr. N.N. Purtova LLM MSc (Coördinator and lecturer)

mr.dr. L.A. van Noorloos (Lecturer)

dr. K. van Aeken (Lecturer)


Doel van de cursus (alleen in het Engels beschikbaar)

Upon successful completion of this course, the students will be able to:

  • Assess real-life and hypothetical instances of data science and data-driven businesses on the matter of their sustainability and compliance with the principles of responsible innovation;
  • Name and explain data protection principles, core principles and notions of criminal and constitutional law relevant in the context of data science applications.
  • Recognize data protection-, criminal and constitutional law issues relevant in the context of real-life and hypothetical data science applications and data-driven businesses.


Inhoud van de cursus (alleen in het Engels beschikbaar)

Data science has a potential to profoundly and tangibly affect business and society. Mining growing pools of data using advanced algorithms promises to generate new insights into human behaviour and provide solutions to a variety of social problems like effective resource management, enforcement of public order, traffic control, accurate and fast diagnostics, and treatment and prevention of disease. The social value of personal data is translated into the economic value. Many successful business models make profit of the ability to (provide) access to, analyse and trade in personal data and data sets, effectively claiming property rights in personal data. At the same time, accumulation of unprecedented amount of data and the new horizons it opens present risks for individuals, groups, and societies. For this reason, it is important that the data science applications are designed and used, and value is extracted from data in a way that is secure and sustainable, meaning that the risks are eliminated or mitigated, individuals are protected, and fundamental values of the society endure in the face of the innovative data processing techniques.

The course will deal with the following issues:

  • Theoretical introduction into the notions of privacy, responsible innovation and sustainability;
  • Legal regime of personal data and privacy in relation to data science
  • Data science and criminal justice, and
  • Data science and constitutional order and democracy
  • Law and strategies of sustainable data science

The lectures will focus on challenges of the use of data science and how law and regulation handle these challenges and secure the affected societal values. These issues will be explained from the perspective of developers and data-based businesses, data science users and data subjects (i.e. individuals whose data is processed by data science applications).


Bijzonderheden (alleen in het Engels beschikbaar)

The reading list for the course will be provided on the Blackboard before start of the course.

To facilitate meaningful discussions in class and help students without legal background understand legal materials, students are expected to read the assigned literature for every lecture to be ready to answer questions about it in class (contributes to class participation).

Written exam: It is a closed book exam, meaning that the students are not allowed to bring any materials to the exam room except for an English dictionary. A resit of the written exam is allowed.

The written assignment is an essay where students are asked to assess how a real-life or hypothetical data science application relates to the principles of data protection, criminal, and/or constitutional law and democracy. Please check Blackboard for precise formulation of the actual assignment. The lecturer will explain the assignment during the first session of the course. The assignment is graded. It is not allowed to re-write the assignment (the written resit will therefore function as a resit for the entire course). The deadlines will be stricktly observed. A good-faith submission of a written assignment is a precondition for admission to the written exam.


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(25-jul-2017)