Complexity Science

Complex systems are much more than the sum of their parts. The UNESCO Chair of Complex Thought Edgar Morin identifies complex systems as those where the complete knowledge about how individual components interact with each other does not guarantee complete knowledge about how the whole behaves. A more scientifically precise definition of complexity remains a formidable challenge even nowadays. Probably some concrete examples can provide a better picture of how complex patterns look like.

A planetarium machine representing the solar system. Even though understanding it could be quite complicated because of its several components,  this machine is not a complex system. In fact the role of its components is not only known but it was planned in order to make the machine work in a certain way. In complex systems the knowledge of the rules according to which individual components behave does not guarantee the knowledge of the behaviour of the system as whole.

Complexity is a paradigm concerned with understanding how global, unexpected patterns emerge from local, microscopic interactions. For instance, the laws of physics from aerodynamics can explain how an individual bird can fly and change its flight direction. Nonetheless the same laws cannot explain how several birds in a flock manage to be together, coordinate with each other and give rise to beautiful ordered shapes. In order to gain insights from such phenomenal coordination it is necessary to investigate the interactions among birds and to think on how these microscopic interactions propagate from bird to bird up to determine the shape of the flock as a whole.

Complex phenomena pervade the experience of our everyday world. Individuals sharing content on social media platforms can give rise to viral videos. Why do some videos go viral while others don’t? Does it depend maybe on the structure of the network of social ties among a certain group of users on the World Wide Web?

Small groups of people moving within a city usually flow along a complex network of public and private transportation means. How do pedestrians in a crowd flow? Can traffic jams originate also without any car accident happening? Does building new roads always decrease commuting time in big cities? How to limit traffic without traffic lights and intersections?

The above are all questions that can be framed within a complex system perspective. Nonetheless, since these questions are relative to such a wide variety of different systems it might be intuitive to think of complexity as an interdisciplinary paradigm. This is one of the main challenges of current research on complex systems: in order to really gain insights on the observation from the outer world mathematical tools from Mathematics and Physics have to be coupled together with simulations and expertise coming from a wide variety of disciplines such as Chemistry, Biology, Engineering, Social and Cognitive Sciences among several. Complexity theory challenges the usual boundaries of academia by requiring for scientists with different expertise to establish new links and thus make science advance. The best example of it is the Santa Fe Institute, New Mexico (US), whose multidisciplinary research environment resulted in cutting-edge advancements on the theory of complex systems and several Nobel-prizes as well.

Given the recent technological advances, complexity theory is currently booming within the scientific community mainly for two reasons. On the one hand, theoretical advances can now be corroborated and further generalised with extensive numerical computations, made possible by clusters of supercomputers. On the other hand, this is the relatively new “age of data”, where massive datasets about biological, social and technological systems get collected and released at a steep rate. Having large datasets that can be checked by increasingly sophisticated algorithms is quintessential for shedding light on the mechanisms behind complexity.

All in all, complexity science has to be considered the “missing link” between disciplines interested in the observation of our world. Mathematical tools, simulations and field-specific expertise work in synergy within a complex systems approach to explaining how the world works. Outreach programmes usually put together researchers and students for trying to make complexity known also by students in their early educational stages and this is what Complex Forma Mentis aims for as well.

Further Readings:

Morin, E. (2008). On complexity. Hampton Press (NJ).

Mitchell, M. (2009). Complexity: A guided tour. Oxford University Press.

Johnson, N. F. (2007). Two’s company, three is complexity: A simple guide to the science of all sciences. Oneworld Pubns Ltd.

NetSciEd Team (2016). Network Literacy: Essential Concepts and Core Ideas. Available online in 19 languages.

Cramer, C., Sheetz, L., Sayama, H., Trunfio, P., Stanley, H. E., & Uzzo, S. (2015). NetSci High: bringing network science research to high schools. In Complex Networks VI (pp. 209-218). Springer International Publishing.