DS816: Ethics by Design

Study Board of Science

Teaching language: Danish or English depending on the teacher
EKA: N340067102
Assessment: Second examiner: Internal
Grading: 7-point grading scale
Offered in: Odense
Offered in: Autumn
Level: Master

STADS ID (UVA): N340067101
ECTS value: 5

Date of Approval: 05-11-2019


Duration: 1 semester

Version: Archive

Comment

DISCONTINUED - offered last time autumn 2020.
The course is offered for the first time in autumn 2020.

Entry requirements

A Bachelor’s degree or a Bachelor of profession.
The course cannot be taken by students enrolled in the master programme in Computer Science

Academic preconditions

The course is introductory.

Course introduction

The aim of the course is to enable the student to analyse data ethical issues as well as it-ethical problems in relation to artificial intelligence and apply value sensitive design methods. This is important to pro-actively embed ethical values in the design phase.

The course provides a foundation for applying the knowledge, competences, and skills, which are acquired in the education, particularly addressing issues related to data-ethics, value sensitive design and it-ethical problems in artificial intelligence.

In relation to the competence profile of the degree it is the explicit focus of the course to:
  • give the competence to handle work- and development situations such that issues concerning data ethics, it-ethics and artificial intelligence are pro-actively integrated in the design phase.
  • give skills to analyse and reflect upon issues related to data ethics, it-ethics and artificial intelligence, as well as apply value sensitive design methods.
  • give knowledge of methods to identify and handle problems related to data ethics, it-ethics and artificial intelligence.
  • give knowledge about data ethical and it-ethical issues, such as e.g., fairness in algorithms, transparency, profiling, responsibility, and value alignment in AI.
  • give knowledge about theories about data ethics, it-ethics and artificial intelligence and value sensitive design methods.

Expected learning outcome

The learning objective of the course is that the student demonstrates the ability to:

  • analyse problems related to data ethics and it-ethics and artificial intelligence.
  • have knowledge of value sensitive design methods.

Content

The following main topics are contained in the course:

  • Philosophy of technology.
  • Value sensitive design methods.
  • Big data and data ethics.
  • Artificial intelligence and ethics.
  • Fundamental machine ethics.

Literature

See Blackboard for syllabus lists and additional literature references.

Examination regulations

Exam element a)

Timing

January

Tests

Oral exam

EKA

N340067102

Assessment

Second examiner: Internal

Grading

7-point grading scale

Identification

Student Identification Card

Language

Normally, the same as teaching language

Duration

Preparation 20 minutes

Examination 20 minutes incl. grading.

Examination aids

All allowed.

ECTS value

5

Additional information

The student picks a random exam question in the course syllabus before the preparation time. The exam starts with a 5-minute presentation and hereafter there will be a discussion between the examiners and the student, primarily based on the exam question and the presentation, but the student must also be able to relate to other topics from the course.

The examination form for re-examination may be different from the exam form at the regular exam.

Indicative number of lessons

26 hours per semester

Teaching Method

The teaching method is based on three phase model.
  • Intro phase: 13 hours
  • Skills training phase: 13 hours, hereof tutorials: 13 hours and laboratory exercises: 0 hours
Activities during the study phase:
  • Case-work.
  • Preparation of lectures.
  • Preparation of presentations.

Teacher responsible

Name E-mail Department
Anne Gerdes gerdes@sdu.dk Institut for Design og Kommunikation (00)

Timetable

Administrative Unit

Institut for Matematik og Datalogi (datalogi)

Team at Educational Law & Registration

NAT

Offered in

Odense

Recommended course of study

Profile Education Semester Offer period