Scale, Geoffrey West

 Scale should be essential reading for any scientist.  It opens the door to new concepts that could lead to a paradigm shift in the 21st century, such as big data and the science of networking.  Yet these are only peripheral to the main thesis.  Geoffrey West's premise is that there are biological axioms that scale according to size, which can be applied to things not usually considered alive, such as cities and companies. 

First, he provides the hard biological evidence for axioms of scale.  Metabolic rate is one of many examples that are best described as intangible biological fractals pervading the universe.  Other examples are heart beats, white/grey matter, insect/colony biomass, longevity, and neural and circulatory systems.  Remarkably, the size of these systems scale at multiples of 1/4, no matter what animal is being referenced. 

Things that typically aren't thought of as being alive are considered, such as vehicles, cities, and companies.  Did you know that the average car combusts roughly a billion times during its lifespan, which is only slightly lower than the typical number of heartbeats of any mammal?  I certainly don't consider this evidence of cars being alive, but I am open to there being universal laws that describe lifelike systems such as a car. 

Likewise, I think it's a mistake to call cities and companies alive because they can't reproduce.  In my mind they better serve as a metaphor for body systems.  I used to think the ability of something to resist entropy was the only thing that defined it as being alive; but reproduction is critical too, because not doing it effectively ends the chain of life.  There can't be life if there's no way to pass down the information needed to reconstruct itself. 

Another interesting thing he covered are called Dunbar’s numbers, which are limits to group sizes in social interaction.  Social connectivity in cities scales at 1.15 for a number of metrics, including cell phone usage (think of conference calls and social networking).  However, invariance was measured in the number of friends, meaning it doesn't scale- someone in a small town would have just as many friends as someone in a city.  It means that Dunbar’s limits apply; that the diversity in cities makes it easier to identify with people we have things in common with. 

What does this mean for the future of science?  It means that big data is taking over.  It's getting harder for scientists to test and prove theories, because there's so much data now that algorithms are getting more efficient at discovering natural laws.  It would take a human all day to sift through 100 pages of data, but a computer that could "see" it automatically is more likely to find the right information: probably information the scientist wasn't even looking for.  The ideas in Scale are so big that only computers can simplify the complexity of comparing systems in humans, cities, and companies to formulate cohesive principles of growth.