It may seem redundant to say this, but your brain is not a computer. It never has been and it never will be. Your consciousness won’t be downloaded into a computer in yours or my lifetime.
Computers are technology-based tools that only do what they are told (programmed) to do. Your brain, on the other hand, began life with a set of reflexes it was never taught. Your brain re-experiences things in order to for you to remember, but it doesn’t store those memories in anything that looks or acts like a computer’s storage device.
In short, your brain is not a computer. It’s time to put this analogy to bed.
I’ve long been uneasy with the analogy that cognitive and neuroscientists have been foisting on the brain — that it is very much like a computer — since my childhood. As someone who’s been deep into computers all my life, it just never seemed to make much sense to me. Computers don’t think for themselves, they can’t do anything that you don’t explicitly tell them to do, and they don’t have any inherent reflexes or skills built into them. Computers are literally giant doorstops if they don’t have an operating system.
While there appear to be some shallow similarities between the two, once you scratch the surface a bit, those similarities disappear. Robert Epstein, a senior research psychologist at the American Institute for Behavioral Research and Technology, put my belief into a thoughtful, well-reasoned essay over at Aeon recently:
Senses, reflexes and learning mechanisms — this is what we start with, and it is quite a lot, when you think about it. If we lacked any of these capabilities at birth, we would probably have trouble surviving.
But here is what we are not born with: information, data, rules, software, knowledge, lexicons, representations, algorithms, programs, models, memories, images, processors, subroutines, encoders, decoders, symbols, or buffers — design elements that allow digital computers to behave somewhat intelligently. Not only are we not born with such things, we also don’t develop them — ever.
Indeed, we have little idea of how the human brain works and instead rely on analogies to help inform and guide our understanding. But if the analogy doesn’t really hold water, it begins to lose its usefulness in guiding experiments and cognitive models. Instead, the analogy can become a self-made prison that limits our ability to grasp concepts that don’t fit into the analogy.
Sadly, most cognitive and neuroscientists studying the brain today still work — and even revere — this limiting model of brain-as-computer.
A few cognitive scientists — notably Anthony Chemero of the University of Cincinnati, the author of Radical Embodied Cognitive Science (2009) — now completely reject the view that the human brain works like a computer. The mainstream view is that we, like computers, make sense of the world by performing computations on mental representations of it, but Chemero and others describe another way of understanding intelligent behaviour — as a direct interaction between organisms and their world.
The brain is more complicated than most of us can even imagine. While technology engineers readily understand all the parts that go to make up a computer, cognitive scientists don’t know the first thing about how the brain does even the simplest of tasks, such as storing a memory, learning a language, or identifying an object.
You know all of those thousands of research studies that rely on Functional Magnetic Resonance Imaging (fMRI) that produce those millions of color pictures of the brain lighting up when it’s doing something? They tell us virtually nothing about why those parts of the brain are lighting up, nor why that would be important.
Imagine taking a person from 300 BC and introducing her to a modern electrical switch connected to a lightbulb. She can turn the switch off and on and see the impact of that behavior on the light. But it would tell her virtually nothing about how electricity works, nor anything about the component parts of electricity. That’s what fMRI scans of the brain are to researchers today.
Think how difficult this problem is. To understand even the basics of how the brain maintains the human intellect, we might need to know not just the current state of all 86 billion neurons and their 100 trillion interconnections, not just the varying strengths with which they are connected, and not just the states of more than 1,000 proteins that exist at each connection point, but how the moment-to-moment activity of the brain contributes to the integrity of the system. Add to this the uniqueness of each brain, brought about in part because of the uniqueness of each person’s life history, and Kandel’s prediction starts to sound overly optimistic. (In a recent op-ed in The New York Times, the neuroscientist Kenneth Miller suggested it will take ‘centuries’ just to figure out basic neuronal connectivity.)
I’ve often said we’re are at the same place 18th century medicine was in understanding the human body and the disease process. It wouldn’t surprise me that it could take another 100+ years before we have even a rudimentary understanding of the brain’s actual processes.
We’ve come a long way from the junk science of a “chemical imbalance in the brain” (as constantly parroted by pharmaceutical companies in the 1990s and even 2000s, long after the theory was disproven) to help explain why mental disorders exist. Dedicated researchers are working hard every day to try and unravel the mysteries of a human’s most important organ.
Realistically, though, we still have a much longer way to go in order to answer even the most basic questions of brain functioning. This essay is a good reminder why we should only keep an analogy as long as it seems to fit with known facts. What we know about human behavior suggests it’s time to move on from believing our brains are like computers.
For further information
Read the full Robert Epstein essay over at Aeon: The empty brain (at over 4,000 words, it’s not for the faint of heart)
from World of Psychology https://psychcentral.com/blog/archives/2017/08/04/your-brain-is-not-a-computer/
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