Learning objectives Part B

What you will learn in part B of the course  (module 3 and 4) is:

• The key elemenst of  complexity theory (like uncertainty, emergent  and unexpected behavior) and its importance for understanding complex problems.
•  The implications for governance and decision making in such an environment.
• The process of  translating  public values in regulation  and underlying problems: what are the pitfalls?
• The main conditions for effective regulation of infrastructures  and what might go wrong.
• Some practical tools to enhance your managerial and decision making skills when dealing with complex problems.

Content module 3

This week is all about complexity theory . This will be done by one of the leading experts in this field: Eve Midleton Kelly from the London school of Economics.

A complex system is defined as one in which many independent agents interact with each other in multiple (sometimes infinite) ways. This variety of actors also allows for the ‘spontaneous self-organization‘ that sometimes takes place in a system. This self-organization occurs without anyone being in charge or planning the organization. Rather, it is more a result of organisms/agents constantly adapting to each other. The complex systems are also adaptive (i.e., they always adapt in a way that benefits them).

Another important concept in complexity theory is that there is no master controller of any system.

In short, we have to deal with a lot of uncertainty and  many actors with different interests. In module  4 we will explain the huge implications in terms of governance and decision making (with a focus on infrastructures). We will discuss  some pratical tools to deal with such situations!

After the web lectures in this module you will understand the picture below.