Institution
Kaunas University of Technology, Faculty of Informatics

Web Site
https://fi.ktu.edu/

Factual description
“Artificial Intelligence and Decision Making” is a course in Master’s degree programmes in Informatics and Mathematics.
Within the scope of the course, complex systems are considered as IT systems combined of different components with unique functionalities. Although each component is designed and implemented separately, they have specific uncertainties which should be processed regarding the properties of the global system. Implementation of such systems require prior technical knowledge. Selection of optimal properties for each component should be performed with respect to the economic aspects and sustainable development. For example, high resolution images are better for image recognition systems, but the hardware required to capture, store, and process high-quality images is much more expensive and can result in a waste of resources.
The course material focuses on the “decision-making component”. Students analyze different algorithms and combine theoretical knowledge with practice in their individual works. Another task is to work in groups and to develop a specific system which can be applied to solve a particular task. In this task students face the need to properly design the components and make the overall system both economically viable and environmentally sustainable.
Moreover, only the big idea is provided to students by the challenge owners (usually, business partners). Students discuss various aspects of the given field and identify a particular problem (challenge) which can be solved by using the course material and therefore help to create a sustainable environment.
When solving close-to-real problems, students must ensure that the data used in the created system has been collected without violating the law. Another ethical issue is biased data. If such data continues to be used in making decisions, it replicates biased decisions and does not guarantee equal opportunities for all regardless of gender, race, ethnicity or other features. The course material covers the ways to construct an impartial decision-making mathematical model, the concept of ethical artificial intelligence, and how not to harm the environment and the community by solving a client's task.

Relevance in complex systems
Students work in groups to identify and solve a particular problem in the given field with respect to various aspects (social, economic, technical, ethical, etc.). They develop knowledge in the field of artificial intelligence (AI) by analyzing distinct AI methods in the experimental environment and applying them in close-to-real-life environment in which separate components of data preparation, AI application and interpretation of the results should be treated as an integral system with appropriate links.

Strong points
The strong point of this course is the challenge-based learning approach, which combines working in group, collaboration with the business partners and developing a prototype in close-to-reality conditions.

Transferability potential
The transferability can be performed by the means of the learning methodology (challenge-based learning). However, cooperation of teaching institutions and business is not always easily organized. In this course students learn to consider various aspects of the problem and this helps them to become responsible citizens and therefore create a sustainable and ethical environment.