Ethics of AI

There are no prerequisites for the course. Elements of AI (TKT21028) is recommended as a good introduction to artificial intelligence. 

After the course you

• understand the role of ethical thinking in the planning and implementation of AI systems,
• can describe different ethical aspects and considerations of AI,
• can analyze the risks and opportunities of AI solutions from an ethical perspective,
• can detect when ethical considerations are needed in AI solution implementation,
• can follow the ethical discussions in public and in expert communities,
• know the existence of ethical guidelines and are able to apply them in straightforward cases, and
• understand when the ethical issue requires additional expertise. 

The online course material is intended to be self-contained. Links to additional, optional readings are provided in the material.

Target group

The course is suitable for

• anyone interested in ethical questions related to artificial intelligence
• all students in any study programme

No particular computer science background is required, but it is recommended that you are familiar with basic concepts such as machine learning. For a good introduction to artificial intelligence, the course Elements of AI (TKT21028) is recommended. 

• The course can be taken at any stage of studies.
• Intermediate level course in Computer Science. 
• The course may be offered among the university’s continuous learning courses.
  

Completion methods

• The course is completed online (fully distance learning) and there are no attendance requirements.
• The course is completed by doing exercises. All the exercises are automatically or peer graded. There is no exam. 
• The detailed criteria for passing the course are described in the MOOC online learning environment. 

Open University and degree programme completion methods may be different.

Contents

The course content consists of text, visual and interactive elements that are available online.

1. Introduction (what is AI ethics)
2. Do good? (Beneficence and Non-Maleficence)
3. Accountability: Who should we blame?
4. Transparency: What should we know?
5. Privacy, Security…: Human Rights 
6. Fairness: Why should AI be Fair? 
7. Future Challenges
8. Putting it together

Assessment practices and criteria

Successful completion of the exercises in the MOOC. Criteria for passing are defined and described in the MOOC learning environment. 

The course is graded on a pass / fail basis.

Activities and teaching methods in support of learning

• The course material contains text and interactive elements.
• The exercises are designed to challenge the student to re-read the material and access further sources enough to be able to solve the task.
• Students own thinking to apply ethical concepts in assignments is required.

Recommended optional studies

• courses in the Master of Data Science and Master of Computer Science programs give much technical perspective.
• Introduction to Ethics at the Open University and courses in philosophy and social sciences faculty go deeper into the ethical aspects

Additional information

The course is part of Sustainability Studies Network(Opens in a new tab).