Societies have developed over a long period of time, much like how species develop due to natural selection. As a result, the development societies show a remarkable amount of similarities to the evolution of biological beings. With this in mind, it is not a stretch to consider our social, economic, and political systems to be biological. A biological framework provides an intriguing structure into how we can view and analyze the complex and adaptive systems of societies since parallels can be made between ourselves and natural laws. Just like biology, societies are so complex that they cannot be fully measured at this time, however, data science can revolutionize how we measure since it allows us to analyze data sets and make conclusions on incredibly large scales. Data science can help us understand complex adaptive systems better than we could have ever before since it presents a way to organize and analyze the immense amount of data that comprise these systems.

Societal creations such as cities seem to follow natural laws of life, such as scaling laws. Data science methods such as the impedance method for human movement implement a framework derived from Ohm’s Law, a natural law. Cities have been shown to scale exponentially in factors such as GDP, infrastructure like gas stations, and even crime and disease. When related logarithmically, these factors are essentially linear, showing a common exponential scaling factor. Mammals show similar relationships with heart rates and size, and also have a common exponential scaling factor. This relationship between natural laws, and complex adaptive systems and biology, shows that cities likely follow natural laws much like organisms. The impedance model for human movement takes this idea one step further and bases its framework on Ohm’s Law, a natural law regarding the flow of electricity. By changing the individual variables, the subject of the law is changed from electricity to diffusion of human populations. Not only is the concept of this model intuitive given the idea that humans and societies will work in similar ways to the natural laws of the world, but it is also more accurate than previous methods such as the gravity model and does not require the use of parameters which could implement bias. The accuracy of this model suggests that data science can predict population-scale trends based on a population-size data set, in this case, CDR data. Also, it shows possible links between data science techniques and natural laws, which could lead to further development of data science methods that are rooted in natural laws.

In the vein of understanding the nature of complex adaptive systems such as cities and how they relate to biology, data science has provided the ability to gain insight into how cities and regions function. Organisms are made up of an assortment of cells and ways to move and process resources in and around those cells. People act similarly, with relationships between other people and how they move. One example of this is the fractal nature of cities and how it relates to the fractality of the circulatory system. The circulatory system how nutrients can move throughout our bodies via our bloodstream. Some passageways are bigger, arteries, and others are smaller, capillaries. Also, for intensive purposes, the heart is the home base of the circulatory system so it receives the highest traffic of blood in the body. Road systems are similar to the circulatory system, with a base and other roads and highways that act as paths throughout the body, which could be a national road system. As shown by a map compiling trucking routes originating from Laredo Texas, highways act as arteries and smaller roads act as capillaries. Upon viewing the map it becomes abundantly clear how similar it is to the circulatory system. Although not as complex as modern data science methods, to develop this map an immense amount of trucking data must have been analyzed and presented, which is data science at the end of the day. This again shows how data science can help relate our societies to biological systems and all the subsequent implications.

Using the idea that organisms and our societies were developed with essentially the same process, biological and natural laws can be applied to complex adaptive systems. Data science can take from this idea and provide ways to both reinforce this idea by uncovering population-wide trends such as scaling or fractality, and also use natural laws such as Ohm’s Law to describe humans instead of electricity. With data science as a tool and biology as a framework, we can develop analytical tools to understand the largest scales of society at national and higher levels. This can be monumental in human development since more people can be added into data sets, and increasing the sample size used in algorithms will make them more accurate. Also, the removal of some bias involved in choosing what samples to use will benefit underrepresented populations since individuals will have just as much say individually as a person from a more represented population depending on the scale of the data used in a data science algorithm. As data science methods become more accurate they will be able to help more people by providing more accurate insight into problems such as infectious disease or inequalities. Data science can be used irresponsibly, however, since all it provides is better insight into certain issues, and is not a solution in and of itself. As a result, if someone did have malicious intentions, data science tools could help them. Overall, data science has incredible implications for improving the human condition since we can monitor our progress and paths forward better than ever before. Methods that implement CDR data, for example, can help us predict infectious disease rates and population mobility better than ever before which can be used to greatly speed up responses to public health emergencies and improve the efficiency of responses. This is just one example of the possibilities that data science presents. Overall, it can provide us with the insight necessary to better understand situations on a global scale, and that can be used to further improve people’s lives in meaningful ways.