In class questions 2

Why are humans better at understanding patterns than processes?

The human brain, unlike a computer, consists of a great many relatively slow processors working in parallel. Consequently, the human brain is much better at doing a bunch of similar operations in parallel than in doing a series of operations in sequential order. As a result, a lot of human cognition involves doing calculations in advance and storing answers; then in the moment attempting to match the situation at hand to the predetermined situation it most resembles.

How do systems store information?

Systems store information by creating self-perpetuating patterns within themselves: for example, Florence “stores” the relationships and people that constitute the silk trade in the particular spatial pattern of the silk neighborhood.

How do systems learn?

Systems learn by changing in reaction to stimuli, storing some information about successful and unsuccessful responses that allows them to successively refine their approach over time in pursuit of certain goals. Learning is associated with intelligence, and therefore implies that the changes in the system are directed towards some purpose (survival or otherwise).

How do systems adapt?

Systems adapt by changing in reaction to stimuli. Unlike learning, adaptation does not imply either a purpose or the successful approximation of that purpose: any change a system undergoes without collapsing can be thought of as adaptation, whether or not it represents any sort of improvement (improvement implies goal-seeking) or increase in stability.

What are the opposing forces that “keep the drift and tumult of history at bay”?

The force which keeps the drift and tumult of history at bay is the “stickiness” of self-organizing systems. They generate internal forces which preserve their structure in the face of external challenges, adapting and learning to survive.

In-lecture Exercises from Week 1

Definitions
What is a system?
A set of interacting parts that constitute a larger whole.

What is a complicated system?
A system with many parts, but its outcomes are relatively stable and predictable. Consequences from altering parts within the system are predictable.

What is a complex system?
A complex system is one in which small changes in how the system works can lead to large changes in outcome (the butterfly effect). Consequences from altering the system are not predictable.

What is a complex adaptive system?
A complex, adaptive system is one that can change over time, developing new patterns and outcomes in response to changing constraints, moving from stable to unstable states.

On Davidson’s piece:

Adam Davidson describes the difference between an equilibrium perspective and a complex adaptive perspective through the idea of the “Lump of Labor Fallacy”: people imagine that there is a set amount of work to be done, and that as one person enters the labor force, someone else must be pushed out. This is an equilibrium perspective. Davidson argues that this is fundamentally wrong, because the amount of labor is not fixed but is rather dynamic: as people enter the workforce, they are also entering the consumption pool as well, and increase not just the number of people looking for work but also the amount of work that needs doing. For Davison, labor and demand exist in a complex, adaptive relationship: changes in one end up changing the other as well.

 

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