What I've Been Reading

Complexity science does study something distinctive - namely the emergent features of systems that are composed of a lot of components that interact repeatedly in a disordered way. The reason why it has been hard to identify what is distinctive about complex systems is that there are many different kinds of emergent properties and products of complex systems, and they are not all found in all complex systems. The common features of complex systems manifest themselves differently in different kinds of systems. 

What is a Complex System? by James Ladyman and Karoline Wiesner. 

This is one of the most important books you will read in your life. Developing even a rudimentary understanding of the complexity and complex systems will make one look at life differently (for good) plus it will help develop a sense of humility and gratitude for what we have without believing in magic and conspiracies. 

The complex system helps in understanding things such as how animals sufferings in factory farms will lead to a pandemic that could wipe out our species. 

Ladyman and Karoline attempt to "unpack" complex systems by avoiding biases put forth by existing researchers and keeping it open-ended as humanely as possible. They have also kept math and technical details to the minimum.  

They have done an enormous favor to a common reader by defining some of the salient features of the complex systems (not all always applies to all complex systems):

1. Numerosity: complex systems involve many interactions among many components. 
2. Disorder and diversity: the interactions in a complex system are not coordinated or controlled centrally, and the components may differ. 
3. Feedback: the interactions in complex systems are iterated so that there is feedback from previous interactions on a time scale relevant to the system's emergent dynamics. 
4. Non-equilibrium: complex systems are open to the environment and are often driven by something external. 
5. Spontaneous order and self-organization: complex systems exhibit structure and order that arises out of the interactions among their parts. 
6. Nonlinearity: complex systems exhibit nonlinear dependence on parameters or external drivers. 
7. Robustness: the structure and function of complex systems is stable under relevant perturbations. 
8. Nested structure and modularity: there may be multiple scales of structure, clustering, and specialization of function in complex systems. 
9. History and memory: complex systems often require a very long history to exist and often store information about history. 
10. Adaptive behavior: complex systems are often able to modify their behavior depending on the state of the environment and the predictions they make about it.

We argue that a system is complex if it has some or all of spontaneous order and self-organization, non-linear behavior, robustness history and memory, nested structure and modularity, and adaptive behavior. These features arise from the combination of the properties of numerosity, disorder and diversity, feedback, and non-equilibrium. We argue that there are different kinds of complex systems because some systems exhibit some but not all of the features. 

Chaos is not always complexity:

Complexity is often linked with chaos, and it may be conflated with it, but the behavior of a chaotic system is indistinguishable from random behavior. It is true that there are systems that exhibit complexity partly in virtue of being chaotic, but their complexity is something over and above their chaotic nature. Furthermore, since chaotic behavior is a special feature of some deterministic systems, any dynamical system that is stochastic is by definition not chaotic, and yet complexity scientists study many such systems. 

Measuring Complexity:

Ideas such as "logical depth" measure not complexity but order. Complexity is a multifaceted phenomenon and that complex systems have a variety of features not all of which are found in all of them. This implies that assigning a single number to complexity cannot do justice. 

A variety of different measures would be required to capture all our intuitive ideas about what is meant by complexity. 

- Physicist Murray Gell-Mann

In summary: 

There are many important theoretical questions on which complexity science bears, the most obvious ones concerned with relationships between life and nonliving matter, and between conscious and non-conscious matter. The general implication of our analysis for these matters is that the dichotomy between atoms and molecules and advanced life forms is a very crude way of seeing the many layers of structure that are found at different scales.  The only way to understand the emergence of life is by studying the processes that occur in self-organizing physical systems not just physical structures. 

Once the complexity of nonliving systems, such as the solar system and the Earth and its climate, is grasped in detail, the difference between life and non-life seems to be less of a mysterious leap and more of a continuum. 

When we think about complex systems in the right way, we can abstract from some of their features and understand the simplicity that underlies the wonderful complexity!