Required prerequisite knowledge

Higher Education Entrance Qualification.

For exchange students from NLA’s partner institutions: The students must be studying business administration or a related field of study.

Recommended prerequisite knowledge

A very basic knowledge about AI-tools such as ChatGPT by OpenAI, Gemini by Google, Copilot by Microsoft or other LLMs

Relevance within study programme

Elective course in Bachelor of Business Administration and in Bachelor in Innovation, Marketing and Management.

Introduction

This course gives a basic introduction to the digital economy, digitalization, privacy and artificial intelligence. We will take a closer look at different digital information systems, their role in society and digital responsibility. We will discuss whether the tech companies can build robust, ethical, and human-aligned systems that can be trusted, and how AI and other technologies can be exploited by today's businesses. The students will be exposed to and participate in discussion of relevant ethical questions for digitalization of the society and businesses.

Learning outcomes descriptors

Knowledge

The student

• has knowledge of the digital economy, and the importance of digital services for private and public activities
• has knowledge of what characterizes a digital information system, large language models, and artificial intelligence
• has knowledge of ethical challenges, including privacy, vulnerability and data security

Skills

The student

• can work independently with practical problem solving based on the theories, methods and techniques
• can consider the pros and cons when choosing and using large language models (LLM) and AI for different applications and use-scenarios
• is able to write an assignment that contains both the student's own writing and LLM-text, and explain how the assignment was made with references to sources and tools.
• can use tools to assess or evaluate risk in a cybersecurity context

General competence

The student

• has the ability to recognize opportunities and challenges related to digitalization in organizations
• can communicate key topics within the subject area by writing a text
• can identify and reflect on ethical issues of relevance to digitalization
• can discuss ethical questions, including costs and benefits by using AI-based and other digital applications

Content

Topics:

• The digital community and the digital economy
• Business systems
• Digitalization and digital devices
• Digital business operations
• Development and acquisition of digital solutions
• Operation of digital information systems
• Large Language Models (LLMs)
• AI and digital responsibilities
• Methods and techniques for the realization of organizational gains
• Digital literacy and the value of personal data for businesses and citizens
• Inclusion, universal design and digital exclusion
• Privacy, data security and vulnerability

Teaching and learning methods

Lectures. Active students’ participation. The students give relevant example from media and society as an introduction to a discussion about the topic of the lecture.

Scope

Expected workload in this course is at least 250 hours.

Coursework requirements

The following mandatory learning activities must be approved before students can present themselves for final assessment:

• 80% attendance in class.
• Write an individual course requirement report on AI or a risk scenario, max. 1500 words (except bibliography). The report should include detailed information about the LLM' that has been used.

If a student fails the assignment, the report (max 1500 words), he or she will be given a second opportunity, in the same academic term, to hand in an improved answer for assessment.

Grading, coursework requirements

Approved/ Not approved.

Final assessment

The final exam is a 3-hours individual school exam

Grading, examination

The exam is graded from A to F with A being the top grade and F being Fail.

Permitted aids under examination

None.

Assessment language

English, Scandinavian Languages and Norwegian.

Practice

None.

Credit reductions

This course overlaps 7,5 ECTS with (4)HSM207.

Course evaluation

The course is evaluated according to the quality system for NLA University College.

Available as Single Course

Yes