034.007 Kettensägen, Codes, Roboter & Co: Diversität und Technikentwicklung
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2019W, SE, 2.0h, 2.0EC


  • Semester hours: 2.0
  • Credits: 2.0
  • Type: SE Seminar

Learning outcomes

After successful completion of the course, students are able to assess the impact of technological developments in the field of artificial intelligence on different needs of people and critically reflect the associated social development tendencies. They can identify potential technology-related exclusion and containment mechanisms and harness that knowledge for their professional and private lives.

Subject of course

The term diversity refers to a multitude of aspects in which people can differ, eg age, gender, origin, physical abilities, parenthood, etc. In technology development, such differences can play a significant role when it comes to the usability and modes of action of Technologies goes.

Teaching methods

In the LV, concrete examples of technology, such as Facial recognition, the topic of diversity and technology development gradually developed. With the help of current examples of technological developments and related public discussions, scientific analyzes / technical texts etc., the relevance of diversity in technology development is deepened.

Mode of examination


Additional information

Please consider the plagiarism guidelines of TU Wien when writing your seminar paper: Directive concerning the handling of plagiarism (PDF)



Course dates

Mon13:00 - 16:0014.10.2019Seminarraum 127 Vorbesprechung
Mon13:00 - 16:0028.10.2019Seminarraum 127 Diversität und Technikentwicklung
Mon13:00 - 16:0011.11.2019Seminarraum 384 Diversität und Technikentwicklung
Mon13:00 - 16:0025.11.2019Seminarraum 127 Diversität und Technikentwicklung
Mon13:00 - 16:0016.12.2019Seminarraum 127 Diversität und Technikentwicklung
Wed13:00 - 16:0018.12.2019Seminarraum 127 Diversität und Technikentwicklung

Examination modalities

Attendance in the preliminary discussion and in all blocks is a prerequisite for a positive assessment. Up to 2 missed hours can be compensated by a replacement.

Course registration

Begin End Deregistration end
23.09.2019 00:00 02.10.2019 23:55


Study CodeSemesterPrecon.Info
066 645 Data Science
TRS Transferable Skills


No lecture notes are available.

Previous knowledge

no requirments