Sociopolitical Hierarchies and Biology

Sociopolitical Hierarchies and Biology

In the book Sapiens, Yuval Noah Harari makes the argument that studying biology is insufficient for understanding human society. We cannot understand the complex human societies and different cultures of the world purely by studying the biology of humans. Testing humans on physiological and psychological metrics does provide us with interesting information, but it doesn’t explain exactly why so many differences are seen across cultures and places. It also doesn’t explain why certain hierarchies exist within different cultures across the globe.
 
 
To understand complex societies, Harari argues, we have to understand history, context and circumstance, and power relations. By doing so, we can begin to understand the structures within societies that shape the institutions that humans have created, and that ultimately shape the behaviors, opportunities, incentives, and motivations for humans. “Since the biological distinctions between different groups of Homo sapiens are, in fact, negligible, biology can’t explain the intricacies of Indian society or American racial dynamics,” writes Harari.
 
The two examples that Harari uses to demonstrate culture and society relative to biology demonstrate how chance historical events created unique circumstances that shaped different institutions that are highly influential within certain societies, but are unrecognizable outside those societies. Brahmins and Shudras are not understood as different races, but as different castes within Indian society, with substantial discrimination between the two groups. Racial discrimination has been a driving factor of American economic and political society. However, caste systems are nearly completely absent in the United States and the racial discrimination in the United States is not present in India. The explanations for the caste system and the racial dynamics are not biologically based, but culturally based – dependent on power and institutions.
 
Harari writes, “most sociopolitical hierarchies lack a logical or biological basis – they are nothing but the perpetuation of chance events supported by myths.” We see this when we look at recent challenges in the replication of psychological studies. Many of the findings from the field of psychology have come from studies involving college age students in the United States. Such individuals represent a very small segment of humanity. Generalizing from studies involving American college students will give us an inaccurate picture of the world – a picture that is not based on true biology, but on chance cultural factors specific to a unique population. We can easily make the mistake of believing that what we observe, either through a psychological study of American college students or through our own experiences with people in our community, state, or country, reflects a biological reality. However, what we observe is often the result of cultural differences or institutions and power structures that we are not consciously aware of.
 
Harari explains that this is what has happened with the Indian caste system and American racial dynamics. Cultural factors, chance historical events, and subsequent policies and institutions have created differences among people that we can observe and measure. However those differences are not based in biology. It is a mistake to attribute those differences to something innate in Homo sapiens or to assume that the way things are is the way that things should be. Quite often, our sociopolitical hierarchies have no logical or absolute reason for being the way they are.
Cause and Chance

Cause and Chance

Recently I have written a lot about our mind’s tendency toward causal thinking, and how this tendency can sometimes get our minds in trouble. We make associations and predictions based on limited information and we are often influenced by biases that we are not aware of. Sometimes, our brains need to shift out of our causal framework and think in a more statistical manner, but we rarely seem to do this well.

 

In Thinking Fast and Slow, Daniel Kahneman writes, “The associative machinery seeks causes. The difficulty we have with statistical regularities is that they call for a different approach. Instead of focusing on how the event at hand came to be, the statistical view relates it to what could have happened instead. Nothing in particular caused it to be what it is – chance selected it from among its alternatives.”

 

This is hard for us to accept. We want there to be a reason for why one candidate won a toss-up election and the other lost. We want there to be a reason for why the tornado hit one neighborhood, and not the adjacent neighborhood. Our mind wants to find patterns, it wants to create associations between events, people, places, and things. It isn’t happy when there is a large amount of data, unknown variables, and some degree of randomness that can influence exactly what we observe.

 

Statistics, however, isn’t concerned with our need for intelligible causal structures. Statistics is fine with a coin flip coming up heads 9 times in a row, and the 10th flip still having a 50-50 shot of being heads.

 

Our minds don’t have the ability to hold multiple competing narratives at one time. In national conversations, we seem to want to split things into 2 camps (maybe this is just an artifact of the United States having a winner take all political system) where we have to sides to an argument and two ways of thinking and viewing the world. I tend to think in triads, and my writing often reflects that with me presenting a series of three examples of a phenomenon. When we need to hold 7, 15, or 100 different potential outcomes in our mind, we are easily overwhelmed. Accepting strange combinations that don’t fit with a simple this-or-that causal structure is hard for our minds, and in many cases being so nuanced is not very rewarding. We can generalize and make substitutions in these complex settings and usually do just fine. We can trick our selves to believing that we think statistically, even if we are really only justifying the causal structures and hypotheses that we want to be true.

 

However, sometimes, as in some elections, in understanding cancer risk, and making cost benefit analyses of traffic accidents for freeway construction, thinking statistically is important. We have to understand that there is a range of outcomes, and only so many predictions we can make. We can develop aids to help us think through these statistical decisions, but we have to recognize that our brains will struggle. We can understand our causal tendencies and desires, and recognize the difficulties of accepting statistical information to help set up structures to enable us to make better decisions.