Does every human run the same algorithm?

I have been pondering variations of this question for months, for years even. After brushing up on human history, neuroscience, psychology, and taking a few machine learning courses, I started developing a framework through which to answer this question. My first mistaken inclination was to answer with a resounding YES! That is to say, we are running the same algorithm but the only difference was the training data that our minds are exposed to. I came to this conclusion from a few key observations that we, broadly speaking, often take for granted.

For instance, we can generally see how geography is a strong predictor of what language a person speaks, also a person’s ethnicity and religious or cultural affiliations. Of those predicted elements, the most curious is ethnicity, because as we know someone can leave their country of origin and transplant themselves in a new geography and over time adapt to the local norms regardless of their ethnicity, that is to say regardless of their individual biology. This is a very amazing human capability, that is the flexibility of our minds broadly speaking. Of course, in truth some adapt better than others and it’s hard to say why exactly. Are some human brains running a better algorithm or an algorithm that is resistant to change or even thrives on it? You could also argue that a person’s stage in life can better explain how well they adapt, or their sensitivity to opportunity which then could be reduced to another data point to the algorithm than a variation of the algorithm itself.

But, what exactly is the human algorithm? Is it the data and biological processes in our brains or the architecture it is running on, because it is very likely that brains are not the same from a physical standpoint. It’s actually more likely that they are broadly the same, but when you look at the synapses and neurons on a brain, you will come to find there is a very long tail on brain architectures. And not just the neurons and synapses, but the physical size and the configuration of the neural graph. It’s likely that no two brains are exactly alike. We already know that broadly speaking no two faces are exactly alike, or gait or voice and the list goes on, so it would follow the brain is the same. Now the real question is, how does this affect intelligence? I suspect it does affect intelligence, except in broad terms there are certain operations that all brains can approximate like natural language processing. I find this allows me to explain why many deep learning network architectures are able to fit the same data approximately.

So now, I am left believing that humans posses roughly equivalent brain architecture, that allows some uniformity on certain tasks. Said another way, we are all running on a unique brain architecture that is roughly equivalent to the average and thus we enjoy a broadly similar ability to process information. And what is the algorithm? I believe its the topology and the data coded into them. The hardware and the software working together. At the scale of the brain, we can observe it being roughly equivalent across humans, and as the world changes and information flows differently through the graph of human connections, people broadly speaking react to it similarly if you hold the context roughly constant. So in the end the answer is yes and no, but precisely how, is yet to be fully understood. Broadly speaking is how most people have approached this question for millennia, but specifically we are only now developing the tools that could perhaps answer the question more concretely.

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