Societal Consequences of Information Technology (SoCIT)

Course content

Technical systems, no matter how well intended, can often fail in real-world implementation in different ways (consider sundhedsplatformen, MitID, etc). This course will explore the reasons for successes and failures and ways these could be improved or mitigated through approaches that focus on the societal and human context of technology. Students will learn how to engage with complex societal problems when applying computer science techniques, drawing on established theories and practices in human-centred computing. We will reflect on ethical issues and societal consequences of applying computer science methods to address societal problems, and consider relevant strategies and methods based on such reflections for understanding and improving how people intereact with technology.

The course is composed of three modules built around focused project work: 

  • Approaches to problem identification and exploration, including considerations of data and separation of concerns between technology development and human interaction. 
  • Experimenting with prototyping solutions to identified problems, including questions of optimisation, algorithmic correctness, and assumptions of accessibility and usability.
  • Conducting prototype evaluation and reflection, including considerations of the limits of models and discussions of ethics.
Learning outcome

Knowledge of

  • Theories and methods in human-centered computing
  • Current debates on ethics, fairness, and privacy in computing
  • Field methods for identifying and exploring Information Technology problems in society


Skills to

  • Systematically identify problems in society and conduct exploratory research to understand these problems.
  • Prototype and evaluate solutions, paying attention to implications of technical intervention
  • Analyze and discuss potential benefits and pitfalls of computer science methods in relation to rights and ethics in society.


Competences in

  • Reflecting on ethical issues and societal consequences of the application of computer science methods
  • Examining the implications of technical solutions for societal challenges
  • Identifying the relevant computer science methods based on potential ethical issues and societal consequences


Learning activities will include lectures, seminars, workshops, empirical data collection and analysis, user evaluation sessions, flipped classroom and peer feedback sessions, and hands-on clinics teaching students the basics of problem identification and problem space exploration.

Research papers and selected book chapters - See Absalon


Academic qualifications equivalent to a BSc degree recommended

Continuous feedback during the course of the semester
7,5 ECTS
Type of assessment
Written assignment, during course
Type of assessment details
The written assessment will be an individual paper based on the group work. The students will develop a prototype through group work during the course.
The individual exam paper, will describe the development process for the group prototype and reflect on the outcomes.
Both the individual paper and the group-produced prototype description must be submitted.
Exam registration requirements

Three required group assignments must be submitted throughout the course to be eligible for the exam. Assignments will be assessed with a pass/no pass grade and will receive feedback.

All aids allowed

The use of Large Language Models (LLM)/Large Multimodal Models (LMM) – such as ChatGPT and GPT-4 – is permitted for the ordinary exam.

Marking scale
7-point grading scale
Censorship form
No external censorship
Several internal examiners

The re-exam has the same form as the ordinary exam.

If the student is not yet qualified to participating in the exam, then qualification can be achieved by handing-in the three assignments no later than three weeks before the week of the re-exam in order to qualify for the re-exam.

Criteria for exam assessment

See Learning Outcome.

Single subject courses (day)

  • Category
  • Hours
  • Lectures
  • 24
  • Preparation
  • 33
  • Exercises
  • 24
  • Project work
  • 125
  • English
  • 206


Course number
7,5 ECTS
Programme level
Full Degree Master

1 block

Block 1
No limit
The number of seats may be reduced in the late registration period
Study Board of Mathematics and Computer Science
Contracting department
  • Department of Computer Science
Contracting faculty
  • Faculty of Science
Course Coordinator
  • Irina Alex Shklovski   (3-6b637542666b306d7730666d)
Saved on the 24-08-2023

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