KIUA1000 Introduction to AI
- Course codeKIUA1000
- Number of credits10
- Teaching semester2024 Autumn
- Language of instructionNorwegian/English
- CampusHamar
- Required prerequisite knowledge
None
Introduction to AI provides an overview of artificial intelligence, its applications and the ethical considerations surrounding its development, implementation and distribution, as well as themes related to AI, including its history, scope and governance principles. The course also addresses critical questions such as bias, fairness, privacy, accountability and responsibility, all of which play a significant role in the development of AI systems. Through this course, students will not only acquire valuable knowledge but also develop essential skills in research, ethical analysis and decision-making. This gives students the ability to consider ethical dilemmas in AI, propose solutions, assess fairness and privacy considerations and become advocates for responsible AI practices. Overall, the course promotes critical thinking, ethical awareness and effective communication in the context of AI governance and ethics.
Learning Outcome
Upon successfully passing the course, students will have achieved the following learning outcomes:
The student will have
- knowledge of the definition, history and scope of artificial intelligence, as well as the difference between rule-based AI and machine learning and the application of AI in different fields
- knowledge of the principles and importance of AI governance and will be familiar with the ethical challenges and considerations arising from AI development and distribution
- knowledge of biases and fairness issues in AI systems, including algorithmic bias and discrimination
- knowledge of privacy challenges in the context of AI and Big Data, as well as an understanding and knowledge of relevant data protection laws and regulations and privacy-preserving techniques in AI and data analysis
- knowledge of accountability and responsibilities linked to AI systems, including algorithmic accountability and explainability
The student will be able to
- use sources and references, interpret and apply AI in different fields
- assess dilemmas for stakeholders and decide on ethical solutions through ethical analyses
- identify and reduce bias in AI algorithms and data sets, evaluate fairness measurements and implement techniques to ensure fairness and reduce discriminatory results
- assess privacy risks and implement privacy-preserving techniques in AI and data analytics, with the ability to navigate data protection regulations and ensure compliance in AI projects
The student will be able to
- refer to the history of AI and exercise critical thinking and argumentation in relation to the use of AI in different situations
- exercise ethical awareness and sensitivity surrounding the potential impacts and implications of AI
- exercise critical thinking through analyses of complex ethical challenges in the use of AI governance, evaluate different perspectives, balance consequences and propose reasoned ethical solutions
- communicate ethical concerns and recommendations linked to AI governance, as well as collaborating with stakeholders and contributing to ethical discussions in interdisciplinary teams
The course comprises a combination of lectures, practical exercises, independent study and academic supervision.
- two group-based assignments
Compulsory coursework requirements that have been passed are valid for 12 months only. Students wishing to take examinations after 12 months must pass the compulsory coursework requirements again in connection with the next scheduled delivery of the course.
| Form of assessment | Grading scale | Grouping | Duration of assessment | Support materials | Proportion | Comment |
|---|---|---|---|---|---|---|
Written assignment | ECTS - A-F | Group | 100 | • Any use of AI-generated text and content must be clarified with the lecturer, clearly labelled and academically justified in the submission. |
- one project-based group assignment
When taking part in group examinations, all participants in the group will be jointly responsible for all content of the assignment/product/work.
The assignment is assessed using a grading scale from A-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
- Any use of AI-generated text and content must be clarified with the lecturer, clearly labelled and academically justified in the submission