Research Topics in AI Ethics

Postgraduate course

Course description

Objectives and Content

AI ethics is the common reference to a collection of sub-fields in AI developed to respond to the issues of how to manage the moral, personal and societal impact of replacing people tasks and roles with AI powered computing. AI Ethics comprises of four main research sub-disciplines: fair-accountable-transparent AI (FAccT), explainable AI (XAI),responsible AI, and machine ethics (also called artificial morality). 

This course gives an introduction to AI Ethics and a general overview of the state of the art in AI ethics through immersing the students in the research process of an AI ethics topic.  

Learning Outcomes

Knowledge.

  • Identify the basic problems studied in explainable AI (XAI), Fairness, Accountability and Transparency (FAccT), Responsible AI and machine ethics.
  • Understand the premises of the core moral theories.
  • Interpret, explain and extend the need for, and challenges of, AI Ethics.
  • Experience the entire process of research in machine ethics from the inception of an idea, analysis of research work, refining a research question, planing and executing group work and reporting on the work in the form of a scientific report.

Skills.

  • Appraise the ethical aspects of AI problems.
  • Match a specific AI Ethics challenge to its most relevant discipline.

General competence.

  • Reading and explaining scientific articles.
  • Research project management. Scientific reporting

ECTS Credits

15 ECTS

Level of Study

Master level

Semester of Instruction

Spring/Autumn
Required Previous Knowledge
INFO283, INFO284 or INF264 
Recommended Previous Knowledge

INFO282, INFO180 (or INFO283)

Solid background in discrete mathematics and logic. 

Credit Reduction due to Course Overlap
None
Access to the Course
Master in Information Science. Other master students may apply for admission.
Teaching and learning methods
Seminars.
Compulsory Assignments and Attendance

Mandatory participation: Attendance at 80 % of course sessions is mandatory.

Obligatory group and individual assignments throughout the course. 

Compulsory requirements are only valid the semester they are approved.

Forms of Assessment
  • Participation in class discussions 20%
  • Oral individual presentation 30%
  • Group Project  50%

The exam assignment will be given in the language of instruction in the course.

The exam answer must be submitted in the same language as the exam assignment.

Grading Scale
The grading system has a descending scale from A to E for passes and F for fail.
Assessment Semester

Assessment in teaching semester

Students with valid absence as defined in the UiB regulations § 5-5 can apply for an extended submission deadline to eksamen.infomedia@uib.no. The application must be submitted before the deadline for submission has expired.

Reading List
The reading list will be ready before 1 July for the autumn semester and 1 Decemeber for the spring semester. 
Course Evaluation
All courses are evaluated according to UiB's system for quality assurance of education.
Programme Committee
The Programme Committee is responsible for the content, structure and quality of the study programme and courses.  
Course Administrator
The Department of Information Science and Media Studies at the Faculty of Social Sciences has the administrative responsibility for the course