Metaphors and the Human Mind
“Her love was like a summer breeze in autumn; capricious and fickle, yet with warmth to melt the frost nipping about my heart.”
Metaphors have a deep impact on the human psyche. Metaphoric language can encapsulate a complex array of ideas, feelings, and beliefs in a way that we can easily process. As a teacher, I used metaphors to make abstract grammar points more concrete, to aid in memorization, and segue into new concepts. With a few clever metaphors, I could direct the thinking of a large group of students to a specific learning objective.
While my agenda was benign, others use metaphors to manipulate your behaviour to their own ends. Ignorance of metaphors makes you vulnerable to teachers, ministers, politicians, cult leaders, and (especially) marketing companies. As you become more conscious of how metaphors work, you can evaluate if they serve your interests before you choose to accept them.
Cultural Metaphors
From the time that we are children to adulthood, we assimilate thousands of cultural metaphors. Metaphors are like shorthand for thinking and change with the culture. As little as 200 years ago, we lived in an age of superstition. Scores of people claim to have seen demons and angels. Superstitious rituals were used to bring more luck, love, or healthy children. The machinations of goblins explained a blight upon a harvest. These were not whimsical fancies, but the truth as the people understood them. A few hundred years later and we are now in an age of science and technology. We believe our understanding of the world is superior to the dark ages. Physically and mentally, we are very much the same sort of creature we were a few hundred years ago. The Roman culture believed itself superior to all the savage cultures it conquered. We should keep in mind while we believe our scientific way of thinking is superior to all previous cultures, it is very likely that the truth of tomorrow will probably be quite different.
It is natural to have a 100% faith in the cultural metaphors of today and never question them. They form the basic way we understand and interact with our world.
I often hear people say, “Well there are beliefs, and then there are facts.” This is a ridiculous notion. The only reason that we believe in anything is because we have experiences which back up our beliefs. At one point in our past, the world was flat. Everyone didn’t believe that the world was flat; they knew it was flat. It was an absolute fact and the evidence of their eyes told them so. They could see the edge of the horizon and no further, so the earth must be something like a table. Also, when you drop a ball on the ground it didn’t roll, much more like a flat thing than a ball where it would just roll off. The reality of the flat earth was so strong and commonplace that captains risked mutiny if they sailed too close to the edge.
Yesterday, we believed in the superstitious paradigm, today we believe in the scientific paradigm. We still possess an absolute certainty that our “facts” of today are correct, whereas the incorrect facts of past cultures are devalued to “beliefs.”
Today we live in a scientific culture, and we are bombarded with too much information from the Internet. We are more reliant on metaphors simply to condense the overload of information to make it usable and to be able to interact with it. Conscious awareness of how metaphors work and how they control our thinking is even more important in this generation than it ever has been before.
The Age of Science
The universe may or may not be infinite, yet it is larger and more complex than what we can imagine. Scientists observe the motion of planets, moons, stars and believe they are looking at a great clockwork contraption. It may be far larger than anything we can comprehend, but they still believe that they are looking at a mechanism of vast scope and complexity.
The scientific method (a way of looking at the world) has allowed us to surge ahead in our understanding of the physical world and produced thousands of useful applications. Medical progress has extended everyone’s life span, agricultural progress allow us to feed millions, and advances in transportation allow any individual to reach any point on the planet within a few days. In many ways, we are lucky to be living in this enlightened scientific age.
Computer technology has come so far, so fast, that the bulk of our population believe that Artificial Intelligence is inevitable. It is only a matter of time before our most ingenious scientists crack the mystery of the brain. Once solved, we can then replicate a human brain and create a true AI. From there we can create a race of slaves to obey are every command; and as they are machines, we don’t need to be concerned with any ethical problems of how we treat them.
Familiarity and Reality
Mainstream science fiction is full of stories about AI and how we interact with it. We often confuse familiarity with the truth. The more we see something, the easier the idea is to process in our minds. The easier it is to process, the more likely we are to interpret it as truth. The reason that 99.9% of our culture believes in AI is due to familiarity with personal computing devices and repeated stories about AI in the mass media. When you talk with experts actually working on AI research, you get a far different story.
Most experts have adopted the term ML (machine learning) when talking about their research. This choice is, in part, to distance the idea from the popular misconceptions of AI. Everyone thinks AI will be like human intelligence, only far smarter (which lead to the sci-fi stories “Terminator” or “The Matrix”). Machines do have a far greater ability to process a vast array of numbers and learn patterns within the scope of what they are programed to do. They also possess perfect memory, undistorted by emotions. While these are things that humans can’t do, and we see them as points where machines are superior, it is a mistake to assume that they are superior.
Humans have several abilities that no machine can have, the ability to be creative, the ability to set your own directives, and generalized learning. Generalized learning is one of the most under rated super powers humans possess, as all humans can do it. It means that we can learn something in one instance and then apply those concepts to another situation which is related to the first but different in scope. Even simple life forms can do this, yet machines have no ability to operate outside what they were programmed to do. For example: a computer can be programmed to kick the ass of a human grand master at chess. Wow that computer is so smart! But ask that same computer to apply its strategic expertise to a real world military situation and it would fail. Ask it to function like a calculator and it would fail. Ask it for its opinion about chess and it would fail. Machines Intelligence is a worthy study, but it is completely different from human intelligence.
When you spend some time talking to university professors, cognitive development researchers, and the owners of technology companies (aka people who know what F is going on), you discover that we are so far away from producing an AI, they can’t even give a reasonable guess when it might happen.
Nobody wants to hear that AI may never happen. Micro circuit pathways have become so small, the physical size of photons has become a restricting factor. Few people outside the industry know that microprocessors are coming up to the end of upgrades within one or two more generations of improvement. Hardware Engineers are already aware of the problem and looking for workarounds. Research in quantum computers and neuromorphic chips are underway, but these are entirely new ways of creating a computer, not just an upgrade on microchips. Many researchers believe it may take as long as 30 years for neuromorphic chips to catch up to where microprocessors currently are. Quantum computers may be further along, but many companies in development are being very quiet about their current state of development.
This handful of people actually involved in actual research are dwarfed by the throngs of consumers waiting with bated breath to buy their first home robot for their kids. It is exciting! It is progress! Investors dump millions into tech research companies to patent the first working AI. I digress; this discussion is not about AI, ML or even the progress of technology. It is about the human mind; 200 years ago it was a fact that fairies lived in the woods, the earth was flat, and we lived in the centre of the cosmos. Today, we believe AI is around the corner and the exponential growth of technology will continue forever. Yes, the cultural metaphors of today are different from those of the past. The system we use to understand our world hasn’t changed at all; just how we are using it.
The Difficulty in Explaining the Mechanistic Metaphor
Whether AI is in our future or not is irrelevant. The belief that AI as a realistic possibility propagates the mechanistic metaphor. What does “belief in AI” have to do with procrastination? There is a logical connection between the two, but it is difficult to see.
Trying to explain the connection to a person from a technological based culture is like trying to explain the idea of water to a fish. From a fish’s point of view, it was born into a world of water and lives its whole life in water. Water is a perpetual, never changing constant of the fish’s existence, and fades into the background of awareness. Water is not as interesting to the fish as finding prey, avoiding predators or attracting a mate. In much the same way, humans are born into a world of beliefs and thoughts. They influence every part of our lives, just as water does for a fish, yet very few consider why they believe the things they believe in.
Chronic procrastination is a pathology and interferes with ones ability to live a normal life. In 1973, 5% of the adult population suffered from chronic procrastination. In 2018 this statistic has grown to approximately 26%. The belief in the mechanistic metaphor has grown over that time and is responsible for the prodigious increase in both chronic and regular procrastination, which seems to affect everyone. The mechanistic metaphor is so ingrained in our modern way of thinking few notice it and fewer question it.
In bringing this concept to your attention you may be very pissed off with me. My intention is never to alienate you, nor to force you to believe as I do, but to pose ideas for your consideration and to improve your life. Many of the truths we believe are never consciously considered nor reviewed. You hear it, you believe it, and it goes into the background where it controls your life outside of your awareness.
What follows next is a logical case to bring the existence of the mechanistic metaphor to your awareness, explain why we have it, and what it means from the human perspective.
Glossary of Formal Logic
The easiest way to explain the mechanistic metaphor is through a train of logic. If you’re not familiar with formal logic, here is a quick and dirty glossary of terms.
A Premise
This is an idea which we accept as a fact about how the world operates. Often the premise is directly provable, or we have many experiences we can draw upon to establish its validity. Strong premises are not usually questioned.
A Conclusion
When we string several premises together we get a conclusion. The strength of a conclusion depends on the strength of the premises it is based on. Think of a conclusion as a table top and the premises as legs. If the premises are weak then the table falls over. On the other hand, if the premises are rock solid, then our minds have a hard time denying the conclusion.
A Logical Extension
When a strong conclusion is used as a premise for another idea. If X is true, then Y follows.
An Assumption
The scientific method is a philosophy to understand the truth of how the world works. Ideally, a scientist should be emotionally detached from their theories as new observations can drastically change our understanding. However all humans (even scientists) are emotional and we do get attached to pet theories.
“Assumptions” are presented as if they were conclusions or logical extensions, however they have an ulterior motive not related to finding the truth. A person emotionally invested in a belief or theory looks for evidence to support it. They often belittles or ignore evidence which disprove their theory. This is the direct opposite of the scientific method.
Ask yourself the following questions:
1) Is money attached to accepting the belief? This could be a research grant or a sales pitch. Money is an extremely obvious motivator. If the conclusion ends with “And this is why you should give me $10,000…” you know there are assumptions at play.
2) Does the speaker have another agenda other than uncovering the truth? Many non-profit and political groups are promoting a particular way of thinking. They will bias information for their cause.
3) Is the idea emotionally charged? Humans are more influenced by emotion than logic. If the tone sounds emotional, then it is more likely to be persuasive language to pull you into believing one way or the other. Pure logic presents the facts as they are, with a casual indifference whether you believe them or not.
4) Is the speaker willing to let go of their theory if proven wrong? Are they willing to listen to counter points? Do they immediately dismiss evidence that counters their theory? If yes, you are probably facing assumptions over logic.
5) Does the idea make things (thinking, doing, and living) easier? Does it mean someone doesn’t have to change a behaviour?
6) Are they consciously omitting information to support a conclusion?
Logic of the Mechanistic Metaphor
Premise #1: Humans are Tool Using Creatures
One of the defining attribute of being human, is to create and use complex artifacts to solve specific problems, such as hammers, pots, cars, art, clothing etc. Your house is a collection of hundreds of objects, all of which are designed to fulfil specific functions. Use of tools has become integral to our way of life. A human stuck on a deserted island with nothing will start constructing things to make his life easier.
Logical Extension from Premise #1: Humans Love Computers
The more useful the tool is, the more valuable it is to us. At one point in our history, the flint knife was the bomb! Highly useful in jungle survival. Then everyone lost their shit with the innovation of bows and arrows. Fast forward to today and you see everyone carrying cell phones as if their lives depended on them.
Modern computers are among the most sophisticated, versatile, and powerful tools ever been produced. They have a global impact on every aspect of our lives. Could you imagine a day without access to your cell phone, to your laptop or other portable device? No email, social media or TV.
Then there are less obvious places where microchips are used but not called computers. Electronic control mechanisms in your car, in your camera, your washing machine, or the elevator you use. Computers impact your life even when you are not aware of them. They are in systems which bring electricity to your home, keeping records of your money at the bank, coordinating logistic systems to keep food stocked at the stores where you shop. The reason that you could buy a set of knives for $49.95 was because computers were used in the factory to increase quality and bring down the price.
In an advanced language class, students were assigned the task of coming up with an imaginary civilization 100 years in the future. Without fail the students always came up with societies that emulate star trek or star wars. Flying drone cars, better or smaller cell phones, AI robot workers, taller buildings, space ships, and the occasional domed city. Repeating this class for 10 years with hundreds of students, NOT ONCE did they imagine a future that did NOT involve computer technology. We are so caught up with computer technology, most of us can’t imagine life without them.
Premise #2: AI is the Pinnacle of Computer Technology
For this entire generation we value faster, better, improved, upgraded, bleeding edge, computers. Every year there is an improved model. Computer technology has advanced so much over the last 30 years, we have come to expect every year to bring smaller, faster, better machines.
With such progress a fully intelligent machine MUST be coming soon. What could be more cool and exciting than a computer that we could interact with as if it were a fully intelligent human being? AI (artificial intelligence) is the ultimate pinnacle of computer technology, the dream of science fiction made real. How exciting!
If you don’t think AI is the ultimate advancement then ask yourself “What is the next step past AI?” Most would draw a blank or just say smaller, faster, better “I.” Eventually, someone will build an AI tasked to create a better version of itself. As computers can run data sets faster and more accurately than their human counterparts, and should be able to go through thousands of design iterations per hour. Within a short period, they should produce machines with God like intelligence.
Perhaps this “singularity” will decide it no longer needs humans and lead to a horrific dystopian future such as Terminator or Matrix. Or it may become a great oracle with a wealth of information allowing humanity to move into a new state of being.
Is the ultimate point of computer technology… to know God? These questions and their answers may expand into volumes of books on the topic of AI research; but for our discussion here, true AI is an ultimate end point for computer technology.
Premise #3: Natural Intelligence is the Template
How will we know when AI has been achieved? We will compare the computer’s abilities (logic, reasoning, creativity, cognitive adaptability) to those of a natural born human. If it can do everything a human can do, it must be “intelligent.”
This is the philosophy behind the Turing test. Created in the 1950s by Allen Turing, the test involved a human judge communicating with an individual through a chat program. They could either be talking to a human or a computer. If the machine was able to make the judge believe it was a human, then it passed the Turing test. It was considered to be “intelligent.”
Today many programmers still cite the Turing test as a good measure of intelligence. Unfortunately, the Turing test says more about human fallibility than measuring machine intelligence. Any stage magician can tell you that their magic is based on directing perceptions and assumptions of their audience. If you can fool me with a trick does that mean you have magical powers? No. If you can fool a judge into thinking they are talking with a real person does that mean the machine is really intelligent? Also No. To a stage magician, a pass on the Turing test means you have a really good stage act.
True AI will be seen when a machine can learn from its environment and establish its own directives beyond the programming of its creators.
Premise #4: There Are Electrochemical Processes at Work in the Brain
The brain is the part of the human body which “thinks.” We have observed that brain damage leads to a loss of cognitive functions. There are many drugs which can impair your ability to reason. Under close examination there are many subtle electro-chemical processes at work in a living brain.
Psychiatry and neurology are devoted to understanding how the brain works. In the last 20 years, new medical procedures and drugs have eased those suffering with a variety of mental diseases. Because of the success of psychotropic drug therapies we have concluded that there are mechanical components to thinking.
Assumption #1: Thinking is Exclusively a Chemical Process
Chemicals have an impact on the way we think. So researchers assume all thinking is the result a chemical processes. There is no denying that neuro chemistry is an important part of how the brain works. Yet, we don’t know what we don’t know. The exact relationship between the mind and brain still baffles the greatest minds in psychiatry. It is premature to believe that the mind is solely the result of a chemical process.
Problem with Assumption #1
Billions are spent on the development and production of psychotropic drugs, presented as the “solution” to mental disorder. AI research is based on the belief that if a computer is technologically advanced enough, it will start to think on its own. There is an awful lot of money being spent on the certainty that “thinking IS exclusively a chemical process.” This assumption prevents people from looking at the possibility that something else may be going on.
The term “dark matter” relates to a form of matter which lies beyond our ability to perceive it (hence dark). So how do we know about it? Astrophysicists noticed stars at the center of galaxies do not have the pull to account for the size and shape of galaxies that they observed in nature. Something was creating “gravimetric pressure” which allowed galaxy formation. This stuff generating pressure became known as dark matter. Our knowledge of dark matter is exclusively limited to looking at foot prints in the sand. There is no way for us to see it directly, but we can see its effect on other things. Physicists have calculated that dark matter and dark energy account for 99.8% of the mass in the universe.
There is evidence to support the idea that the universe is 99.8% larger than what we can see. There is also a 99.8% chance that the mind exists on a level that we can’t currently interact with. This mind / brain relationship may be analogous to a remote control operator and a drone. Playing with the drone’s circuits will affect its behaviours; in the same way adding drugs to your brain impairs your ability to function. But trying to explain the drone’s behaviour without an operator misses a great part of the story.
You may or may not believe in dualism, however at this stage no one knows enough about the brain to suggest that “all thinking” is “all chemical.”
Conclusion #1 (based on Premise 2, 3 and 4): The road to AI is Through the Brain
The quickest way to create a thinking machine is to reverse engineer a machine that already thinks. The only “machine” which we know thinks is the human brain. So all we have to do is crack the chemical code of neurons, learn how the operating system works and BOOM, we will be able to build an artificial brain.
This massive misconception is due to a global inability to gauge difficulties. There are approximately 1.3 million software engineers worldwide, who understand how computers work. They are dwarfed by 7 billion who don’t. The vast majority who use computers don’t understand how they work nor care to, as long as someone else can repair them if they break. Similarly they don’t know, how their brains work. The inner workings of a computer is just as mysterious as that of their brain; therefor they must be on the same level of complexity. Someone smart can create a computer, therefor someone smart should be able to build a mechanical brain.
Except that a biological brain is light years more complex than a microchip. Neurologists could spend several generations just to map out all the chemical processes in the brain alone. Psychology has stalled in their understanding of multiple models of the mind. The gap is so great, experts can’t even provide a time frame for when we will have an understanding of the brain.
It is as though a tribe landed upon the shore of a great land and wanted to find out how big this new island is. They send scouts up to the top of a mountain and upon their return the chief asks “How long will it take for us to reach the other side?” A reasonable question. Except the scouts saw no beach, no water, just land without end. They are the experts, the tribe is counting on them. How are they to say “I don’t know” and keep their credibility?
Unfortunately this is the same problem with research teams working on AI. They are being financially supported by investors who expect results. Were the investors to hear that it would take 1000 or more years to produce a viable AI, they would withdraw their financial backing immediately.
The number most experts like to use is 30 years. This is far enough into the future that it is almost forever, but close enough to be within the backer’s lifetime. And over a 30 year period perhaps there will be a new breakthrough. It sounds like it is an informed estimate because it’s coming from an expert who has been to the top of the mountain. In reality it is a wild guess to cover up the truth. They really don’t know.
Assumption #2 (based on Conclusion 1): The Brain is a Biological Machine
Researchers often refer to the human brain as a biological computer, because seeing it this way implies that it is something that can be “reverse engineered.” This is not a logical extension, but an assumption because there is a motive to have a possible solution to the problem of AI; thus a reason to collect research grants. This assumption has been in play for such a long time that people believe it to be real.
Logical Extension #1 (from Assumption 2): You are a Machine.
If you accept the idea that the brain is simply a machine, how do you explain consciousness? Is personality nothing more than a program of habitual firings of neural sequences? Is your soul nothing more than a whimsical effect of a 3 pound piece of meat? The benefit of a possible solution to AI carries with it the idea that you are nothing more than a machine.
Premise #5: Machines do not have Choice
Machines are artifacts of humans. They are inanimate objects and they are NOT alive. They do not exhibit any self-motivation present even in the simplest life forms. Machines are designed for a specific purpose designated by a true intelligence; when they can no longer do that function they are considered broken and degrade back into the environment due to entropy. A human machine has no more choice than the nest of a bird or a licking sick a chimp uses to catch termites. A car cannot choose to become a painter. A red pen cannot choose to be blue. Machines are like rocks, they are passive.
Conclusion #2 (from Logical Extension 1 and Premise 5): You Don’t have Choice
Seeing ourselves as biological machines means we are victims of circumstance. Things happen to us and we react to them. We don’t initiate, we don’t create our own reality. The mechanistic metaphor robs us of our freedom to choose our own path.
What’s worse is that brain research is attempting to further this by saying that electrical activity precedes thought. Because it precedes thought, they assume that the electrical activity causes thought. That is an assumption. Even if thoughts occur in a state of matter where dark matter / dark energy resides, the communication of information to the body will still be through an electro chemical reaction in the brain, and that would show up before any other reaction anywhere else in the body.
Assumption #3 (from Conclusion #2): Freewill is an Illusion.
If we accept the idea that all our actions and thoughts are caused by chemical reactions in our brain, then we are nothing more than puppets on strings. We are helpless in choosing the course our life goes. Even the feeling of “free will” is just an illusion created by our neurology to make us feel OK with the fact that we have no control.
There is an awful lot of the universe we don’t know about. The motive behind “Freewill is an Illusion” is an attempt to simplify a very complex system rather than admitting there is a whole lot we don’t understand. There is a great deal of “I don’t know” in the field of neurosciences and it is a very uncomfortable admission for experts.
Except we have Freewill
Except everyone intuitively knows we have freewill. If you randomly smack someone in the face and apologize saying that you were a slave to your biochemical reactions, then the chances are good they would reciprocate with a fist in your eyeball. When the police heard your story, you would probably be charged with aggravated assault. You can argue about determinism till you are blue in the face, but it won’t change the fact that our entire legal system is based on the idea that we all have free will.
Summary – The Nutshell Version
Humans are tool users. Computers are the best tool we have designed. We want better, faster, and more capable computers. AI is the pinnacle of computer technology. We see the quickest way to create an AI is to reverse engineer the human brain. As we think of our brains as a machine which produces thought, we start to think of ourselves as biological machines. Inanimate objects don’t have free will. Therefore you, as a machine, don’t have freewill nor self-motivation. You see yourself as if you were a tool being controlled by your external circumstances. You lose connection with your ability self-determine your own actions.
The mechanistic metaphor is prevalent in every aspect of our modern society and most people believe in, yet have never reviewed the costs of holding such a belief.
In the next two chapters we will look at what holding the mechanistic metaphor costs you and how to free yourself from it.
