Ethical Challenges for AI and AutomationLaajuus (3 ECTS)

Objective

At the end of this introductory course, students will be better able to identify, categorise, and deal with ethical challenges in the business and informatics world. In particular, students will work on some case studies in which they need to make decisions based on the demands of different stakeholders: Management, staff, customers, suppliers, governments, but also society and the environment at large.

At the end of this course, students will be able to
• understand texts on ethical topics and evaluate them in a study and work-related context
• critically evaluate sources and categorise them in terms of ethical viewpoints
• identify ethical challenges in their area of study and work
• formulate their own ethical position precisely and clearly in discussions, argue convincingly, and react to complex arguments of others
• discuss AI and automation-related issues and consequences beyond the field of informatics
• develop and reflect on decision-making processes based on ethical principles
• identify and deal appropriately with intercultural issues in ethical challenges and decision-making

Content

The course will offer a variety of case studies on ethical issues when developing and applying AI tools and automation processes, in particular in a corporate setting. Intercultural differences and implicit bias in decision-making are discussed, as well as consequences of AI and automation implementation for staff, customers, partners, society, etc. The course is very interactive; there will be discussions and group work to exchange ideas and solutions.

Qualifications

No prior knowledge of ethics needed - just an interest in different worldviews and how they can affect ethical decision-making.

Assessment criteria, satisfactory (1)

- Students’ active attendance (3 classes)
- Students’ active participation in class discussions (3 classes)
- Students’ submission of exercises (3 classes)

Assessment criteria, good (3)

- Students’ active attendance (4 classes)
- Students’ active participation in class discussions (4 classes)
- Students’ submission of exercises (4 classes)

Assessment criteria, excellent (5)

- Students’ active attendance (5 classes)
- Students’ active participation in class discussions (5 classes)
- Students’ submission of exercises (5 classes)

Assessment criteria, approved/failed

- Students’ active attendance (3 classes)
- Students’ active participation in class discussions (3 classes)
- Students’ submission of exercises (3 classes)