Syllabus for Data, Ethics and Law

Data, etik och rätt

  • 5 credits
  • Course code: 1DL002
  • Education cycle: Second cycle
  • Main field(s) of study and in-depth level: Data Science A1N, Image Analysis and Machine Learning A1N, Human-Computer Interaction A1N, Computer Science A1N

    Explanation of codes

    The code indicates the education cycle and in-depth level of the course in relation to other courses within the same main field of study according to the requirements for general degrees:

    First cycle

    • G1N: has only upper-secondary level entry requirements
    • G1F: has less than 60 credits in first-cycle course/s as entry requirements
    • G1E: contains specially designed degree project for Higher Education Diploma
    • G2F: has at least 60 credits in first-cycle course/s as entry requirements
    • G2E: has at least 60 credits in first-cycle course/s as entry requirements, contains degree project for Bachelor of Arts/Bachelor of Science
    • GXX: in-depth level of the course cannot be classified

    Second cycle

    • A1N: has only first-cycle course/s as entry requirements
    • A1F: has second-cycle course/s as entry requirements
    • A1E: contains degree project for Master of Arts/Master of Science (60 credits)
    • A2E: contains degree project for Master of Arts/Master of Science (120 credits)
    • AXX: in-depth level of the course cannot be classified

  • Grading system: Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
  • Established: 2020-02-27
  • Established by:
  • Revised: 2022-10-17
  • Revised by: The Faculty Board of Science and Technology
  • Applies from: Autumn 2023
  • Entry requirements:

    140 credits including 75 credits in mathematics and computer science of which at least 15 credits in computer science. Alternatively 45hp in the Master's Programme in Language Technology (HSP2M). Proficiency in English equivalent to the Swedish upper secondary course English 6.

  • Responsible department: Department of Information Technology

Learning outcomes

On completion of the course the student shall be able to:

  • apply different critical thinking frameworks to identify ethical dilemmas related to the analysis of data;
  • analyse the social consequences of data processing in specific application contexts;
  • assess an application scenario with respect to a given legal framework;
  • demonstrate knowledge and skills in dealing with and solving ethical problems in connection with the development and use of digital systems;
  • demonstrate the ability to participate constructively in an ethical dialogue and clearly explain ethical positions, choices and decisions;
  • in writing as well as orally, present one of the studied ethics theories (virtue ethics, utilitarianism, ...) in depth.

Content

Legal analysis of how technical tools in data analysis comply with the legislation. Protection of personal data and privacy, differences and similarities. Protection of intellectual property. The impact of data analysis on the development of legislation. Balancing of various stakeholders' interests and how to address liability issues. The course introduces relevant ethical theories and provides a background in legal aspects.

Instruction

Lectures, seminars and case studies.

Assessment

Active participation in seminars. Oral and written assessment of assignments.

If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the disability coordinator of the university.

Syllabus Revisions

Reading list

The reading list is missing. For further information, please contact the responsible department.

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