This course covers the concept of complexity and its relevance to various fields such as economics, finance. Students will learn about the different types of complexity, including structural and dynamical complexity, and the antecedents that contribute to complex systems. They will explore how judgmental errors and biases can reduce complexity and provide mental models that simplify decision-making processes, but can also lead to systematic errors if not based on accurate information.

The course will examine the implications of complexity. Students will be introduced to systems thinking and system approaches as tools for solving complex problems, and study the works of scholars such as Peter Senge, John Sterman, Jay Forrester, Donella Meadows, Peter Checkland, and Russell Ackoff. They will learn about the hard and soft system approach tools, including causal loop diagrams, stocks and flows diagrams, the iceberg metaphor, and rich pictures, and their applications in understanding the dynamics of crises, the dynamic effects of investments, and debt accumulation. Upon completion of the course, students will be able to analyze complex systems and identify potential solutions using a systems approach.

Lecturer: Sławomir Wyciślak, PhD, Jagiellonian University (Poland)