KIUA2013 AI from a societal perspective
- Number of credits10
- Teaching semester2026 Spring
- Language of instructionNorwegian/English
- CampusHamar
- Required prerequisite knowledge
None.
In the book Atlas of AI, Kate Crawford recently argued that artificial intelligence is neither artificial nor intelligent. The work and resources involved in the systems and infrastructure that create and maintain the machine learning and language processing we refer to as AI are often concealed from the user. This course takes a look at the field of artificial intelligence from different cultural, historical, philosophical and political perspectives. Students will immerse themselves in debates about artificial intelligence in a broad range of social arenas, such as bureaucracy, school, medicine and economics. The course will thematise the application, history and societal impact of artificial intelligence. The course will look at the infrastructure and history of artificial intelligence, but also the potential social impacts of the use of AI in different fields, such as global economic competition, innovation, democracy, political decisions, media, human social interactions and the welfare state.
Learning Outcome
Upon successfully passing the course, students will have achieved the following learning outcomes:
The student will have
- in-depth knowledge of current and historic applications of artificial intelligence in different fields
- an understanding of the resource use and resource creation associated with the use of artificial intelligence
The student will be able to
- apply theoretical perspectives from the humanities and social sciences to analyse the application of machine learning in different fields
- analyse possible consequences of AI-driven automation on labour markets and professional roles, the democratic system and human relations
The student will be able to
- evaluate ethical issues linked to AI-driven data analysis in different fields
- write clearly, understandably and coherently on issues relating to artificial intelligence
Working methods will include lectures, seminars, group work, student presentations, independent study and written assignments. The Canvas communication platform will be used in teaching, as well as a broad range of digital platforms and programs, specifically programs based on machine learning and large language models.
- attendance of at least 80% and active participation in teaching
- a task completed using AI/ML tools
- an oral presentation on a relevant topic of the student’s own choosing
Coursework requirements will be specified in the course curriculum.
Compulsory assignments can be executed and written in Norwegian Bokmål, Nynorsk or English.
- written home examination over three days
Performance is assessed using a grading scale from A to F, where E is the lowest passing grade.
Students are able to choose which language to use for their examination. The available options are Norwegian Bokmål, Nynorsk and English.
Permitted aids:
- Literature
- All printed and written resources
- AI-generated text and content must be clearly labelled and academically justified.
| Form of assessment | Grading scale | Grouping | Duration of assessment | Support materials | Proportion | Comment |
|---|---|---|---|---|---|---|
Home exam | ECTS - A-F | 3 Day(s) | 100 |