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2026/2027  BA-BINTV2601U  Philosophical Foundations of Artificial Intelligence

English Title
Philosophical Foundations of Artificial Intelligence

Course information
Language English
Course ECTS 7.5 ECTS
Type Elective
Level Bachelor
Duration One Semester
Start time of the course Autumn
Timetable Course schedule will be posted at calendar.cbs.dk
Max. participants 50
Study board
Study Board for Professions
Programme BSc in Business Administration and Information Systems
Course coordinator
  • Travis Greene - Department of Digitalisation (DIGI)
Main academic disciplines
  • Information technology
Teaching methods
  • Face-to-face teaching
Last updated on 26-01-2026

Relevant links
Learning objectives
Identify and describe key concepts and influential debates in the philosophy and ethics of artificial intelligence, including theories of intelligence, consciousness, and rationality.
  • Explain and compare different perspectives on the social, ethical, and political implications of AI, such as bias, privacy, accountability, and labor displacement.
  • Apply philosophical and ethical frameworks to analyze concrete cases of AI in business and society (e.g., algorithmic decision-making, autonomous vehicles, workplace automation).
  • Evaluate arguments about the opportunities and risks of modern forms of AI, demonstrating the ability to weigh competing perspectives and evidence.
  • Formulate and defend a reasoned position in oral and written discussion on a contemporary AI-related issue that combines course concepts and independent reflection.
Examination
Philosophical Foundations of Artificial Intelligence:
Exam ECTS 7,5
Examination form Active participation

The completion of this course is based on active student participation in class. The course will be considered as passed if the students participation - based on an overall assessment - in the class activities fulfill the learning objectives of the course. The individual student’s participation is assessed by the teacher.
The student must participate in Presentation(s), A combination of assignment and presentation, Assignment(s), Peer review
Individual or group exam Individual exam
Grading scale Pass / Fail
Examiner(s) Assessed solely by the teacher
Exam period Winter
Make-up exam/re-exam Written sit-in exam
Assignment type: Written assignment
Duration: 3 hours
Aids:Limited aids, see the list below
The student is allowed to bring
  • USB key for uploading of notes, books and compendiums in a non-executable format (no applications, application fragments, IT tools etc.)
  • In Paper format: Books (including translation dictionaries), compendiums and notes
The student will have access to
  • Basic IT application package
Description of activities
Presentation(s): Students will make short group presentations based on applying lecture materials and readings to real-world cases and examples of AI systems.
A combination of assignment and presentation: Assignments consist of short pre-lecture paragraph of each student's prior understanding of the topic and summaries and reflections on group/class presentations.
Assignment(s): Individual and group assignments. Individually students will submit pre-lecture reflections on a philosophy of AI-related topic. As a group, students will submit summaries of class discussions and presentations during exercise. Group membership may change over the semester.
Peer review: Students give feedback on other students' presentations and written assignments.
Course content, structure and pedagogical approach

Artificial Intelligence (AI) is increasingly part of business, society, and everyday life. AI-based tools filter and recommend masses of digital content, drive vehicles autonomously, predict consumer behavior, and even shape global governance. Behind these recent technical developments, however, lie foundational questions about intelligence, agency, rationality, values, and power. This course introduces students to the conceptual, philosophical, and ethical issues raised by AI, with a secondary emphasis on their implications for digitalization and organizational applications.

 

In this course, students will engage with foundational questions related to artificial intelligence, such as whether machines can be said to “think,” and how AI systems influence human decision-making, social interactions, and institutions. The course requires no prior background in philosophy or computer science and may be particularly suitable for students interested in philosophically-oriented job roles at technology companies. Successful course participants should be intellectually curious and enjoy discussing complex and abstract ideas. Students should expect a substantial reading component, which includes a selection of both classic philosophical texts and modern scientific and philosophical articles on AI.

 

Key themes of readings and class discussions include:

 

What is intelligence? Could machines be conscious or creative? What do AI systems reveal about human cognition?

How should we govern AI systems? Can AI systems be biased, racist, or unjust? Who is responsible, morally and legally, for an AI agent’s decisions?

How do AI systems reshape labor markets, privacy, autonomy, and democracy? Could advanced AI pose risks to human flourishing or even survival?
Research-based teaching
CBS’ programmes and teaching are research-based. The following types of research-based knowledge and research-like activities are included in this course:
Research-based knowledge
  • Classic and basic theory
  • New theory
  • Teacher’s own research
  • Models
Research-like activities
  • Analysis
  • Discussion, critical reflection, modelling
  • Peer review including Peer-to-peer
Description of the teaching methods
Focused readings, reflections, and discussions of classic and modern texts and articles on ethics and philosophy of AI.
Feedback during the teaching period
Feedback will be given on students' written assignments and group presentations.
Student workload
Forelæsning 24 hours
Øvelser 14 hours
Expected literature

Course readings may include articles/selections from (but may change):

Marino, G. (Ed.). (2010). Ethics: The essential writings. Modern Library.

Nyholm, S. (2022). This is technology ethics: An introduction. John Wiley & Sons.

Domingos, P. (2012). A few useful things to know about machine learning. Communications of the ACM, 55(10), 78-87.

 

Students without a background in AI and machine learning may wish to consult the following more technical and comprehensive references:

Shmueli, G., Bruce, P. C., Deokar, K. R., & Patel, N. R. (2023). Machine learning for business analytics: Concepts, techniques, with applications in R. John Wiley & Sons.

 

Russell, S. J., & Norvig, P. (2021). Artificial Intelligence: A Modern Approach, 4th, Global edition.  Pearson Education Limited. Harlow, UK.
Last updated on 26-01-2026