The Missing Faculties

Point blank: dopamine addiction causes the suppression of a whole layer of cognitive faculties.

Allow me to elaborate:

Our universe has a property called algorithmic redundancy. What this means is that every little thing does not go off doing its own sweet thing. Instead the whole universe is arranged in patterns. Study one hydrogen atom, and you’ve studied them all. Or a brick, or a ’58 Buick. Or a tornado, which is a pattern of movement, like the DAM  bug (dopamine addiction mechanism) but restricted to a single phenomenological layer. The work of both scientists and poets lies in discovering and describing the patterns that are found in nature.

There is plenty of work for scientists and poets to do. An atom at the end of one of a young girl’s hairs moves in a great many patterns, discovered and described by particle physicists, fluid dynamists, meteorologists, Vidal Sassoon and poets, all at the same time. The universe does not contain just the patterns that people have discovered and described to date, it is absolutely stuffed full of them, and we have barely begun to understand. In any situation, there will be patterns. Peter Senge has recently documented a bunch of them that appear over and over again in different guises in the business world in “The Fifth Discipline”. There are so many of them that being able to see the patterns allows us to chunk up the universe. To handle it with ease, the lazy person’s way. It is this trick that nature has pulled off as her centerpiece of making us smart, and it is what the DAM bug stops.

What natural immunes (people who cannot get hooked on their own dopamine secretions) can do are the following kinds of activities, which all require some sort of feedback – a way of taking the output of something and feeding it back into the input.

Self Remembering

At this moment you are perhaps sitting on a train, or at a workstation, reading this paper. You are “aware” of the paper. But are you also aware of being aware of the paper? Is there a part of you that watches the rest sitting on the train or in the armchair and reading the paper (through the eyes of course, we are not talking excursions to the ceiling here), that when it wants to can control the rest? As you read this, you probably became aware of yourself in just this way. People with healthy dopamine levels always have this “monitor” going in their heads. It’s exceedingly handy because for one thing, it doesn’t get drunk anything like as easily as the rest of our minds. This is why the “hyperactive” and “dreamworld inhabiting” hacker or artist is often in fact the most in control on drinking missions. Not the necessarily the quietest – just the most in control!

The monitor is very important. When you are aware of yourself you can notice when you are making a complete mess of something. You can recognize problems more easily, because you tend to step back and insult your own work while you are doing it! And it is the monitor that is the free and independent you that really does the wanting when you want something. When it wants something it wants it in a big way, and it is something that you find truly fulfilling when you get it. It never stops looking for opportunities. That is why natural immunes will sometimes let projects apparently lapse for years until they find whatever they need to proceed.

The monitor is your real awareness, your ability to spot something that you weren’t expecting to see, but which is happening nonetheless. It is by keeping all our monitors going for longer and longer periods that we will be able to “Consider all that we do, examine every rule, take it back to the rudiments” (as Kate Bush put it) and eradicate the DAM bug. If we know what we are fighting, we can do it.

In order to make the monitor happen, there must be some sort of feedback happening in the brain. Information about the world is gathered by the senses and fed to the brain, which interprets the information and can respond (even while doing “intellectual” work) on full automatic (this is what happens in standby mode). But what is then supposed to happen is that the whole scenario, the picture of the world you started with, but with you now in it as a part of the situation, is fed back into the brain to make sure that what is happening is what was supposed to happen.

Pattern Discovery

We are getting pretty good now at designing computer systems that given the clues, can solve the riddle. The clues may be a bunch of symptoms that a hospital patient has, or the dimensions of a set of boxes to be loaded onto a lorry. What we haven’t really made any progress with at all is designing a computer that can first spot the clues amidst all the irrelevant facts they are hidden in before it has solved the riddle, and then use the clues to solve the riddle. Sometimes even spotting the clues before it even knows there is a riddle.

It’s a uniquely human talent at the moment, that lies behind all new theories of science, as well as the moment of sudden, complete understanding that inspires a poet to capture a thousand summer afternoons in six lines of text.

This ability is based in being able to imagine the relationships of cause and effect between the parts of what one is seeing being arranged in many different possible ways, and then test each arrangement to see if holds up. As we do this we can start to get a feel for how the pieces can fit together very quickly – sometimes only a few hours skillful playing can make the subtle world hidden in whatever one is studying become apparent.

A creative software engineer can take a software problem, chunk it into four or five subsystems, then chunk it again into 4 or 5 different subsystems (which must obviously be connected differently). Then he or she can compare the different approaches and spot the underlying similarities between the approaches, however these are disguised by details of each approach. These are then the real problem – the hard issues that the designer must address to do a good job. And with the problem understood, getting a sensible answer usually isn’t too difficult.

A musical composer or someone doing logistics for a major trade fair can do exactly the same thing. In mathematics, the technique is called inductive reasoning. In the textbooks it is usually shown as a complement or equal to deductive reasoning – step by step stuff. But all mathematicians know better. In fact they do exactly the same thing as a DJ finding the perfect mix for the moment.

The only way to do anything like this with conventional computers is called exhaustive search. We just program the computer to try every possibility, including the vastly overwhelming number of ridiculous ones, and test them. All the experience of chess program designers is that human players do not do this. They find themselves pitting exhaustive searches against something else. The recent ability of computers to function at Grandmaster level in chess doesn’t mean that exhaustive search is now as good as Grandmasters – merely that it is as good as chess.

This trick of holding all the elements of a problem in mind at once and considering each possibility while bearing in mind that as the elements change, the relationships between them also change is very suggestive of a mathematical idea called modal logics.

In modal logics, the value of an expression (or even parts of the expression) can change the relationships indicated by the operators within the expression. Instead of saying,

A + B = C

we can say

A ? B = C

and make the rule that if C is odd the ? becomes a +, but if C is even it must become a -. The odd thing is, we can actually build computers that can cope with this sort of thing. They are analogue machines rather than digital ones. Analogue machines were commonly used for graphics rendering until about 20 years ago, and are not theoretical notions at all.

Analogue machines don’t even have to be electronic. Minimum area problems that would make a Connection Machine cough can be solved by soap films in an instant. The analogue machines that can do modal logics must have a feedback connection in them. The electronics that hold the value of ? must be connected to the electronics that hold the representation of C forwards to fix the value of C and backwards to be fixed by C. The purpose of the circuit is to find a balance or true possibility, not a halt or answer.

The machines have to be analogue because the effect of ? and C on each other must be felt instantly. If the computer was conscious, there would be no period of time in which a process of applying the change could take place. So there would be no sequence of actions that an analogue machine could specify to a digital one to tell it how to do the trick. Of course, the digital computer could be programmed to simulate the physics of what the analogue machine was made of, and do it that way, but it would take a long time. All those atoms to model…

We are here faced with a trick that humans can do, that seems miraculous without feedback being involved in how we do it, but makes much more sense if we assume it is used.

Self Extension

When we discover a pattern, it has a profound way on how we see situations where it is found. When we first encounter a complex situation such as the deck of a yacht or a theater stage, all seems chaos. Later, when we have come to understand the situation, the purpose of each piece of equipment and its relationship to other equipment, all seems simple. The situation has not changed, so we must have. This is one of the reasons why understanding based learning is so much more effective than the usual sort. Instead of memorizing facts in a disinterested state of mind, one gets the subject literally under one’s skin. One in part becomes the area of study, and lessons learned in one situation will always be available in any other.

This is by definition a form of feedback. The mind observes and considers, and what it sees causes it to change. The mind acts upon itself.

Pattern Recognition

When we have learned a pattern by coming to understand it, it becomes very easy to spot it hiding in any other situation. For example, a small and innovative company might be bought by a larger one on the death of the founder. After a period of neglect in unimaginative hands, it emerges triumphant and ends up top of its class. In such a situation, it should be easy for the “Cinderella” pattern to be visible. Indeed, languages used in non DAM bug societies involve exactly this kind of telling of legends as the definitions of words!

Again, there is a physical example of this kind of behavior available, called a tuned oscillator. A tuning fork is an example. Stick a bunch of them in a piece of wood, play a G, and the G fork will ring. When we add a pattern to our repertoire, we seem to do something like set up a tuned oscillator holding it in our minds. Another example simply pumps the oscillator into prominence. This is another example of feedback, since the activity in the oscillator is dependent on the activity in previous cycles plus inputs.

Meaning Based Thinking

Our culture places great value on symbol based thinking. This is presumably because the idea of letting symbols stand for things and then manipulating the symbols seems like a great advance over trying to manipulate brute matter.

It would have taken Hannibal a long time to pile up supplies in front of each of his legionaries and elephants to find out if he had enough to feed everyone before setting off. This is all well and good, but it removes the awareness of the hay bales and pizzas concerned. This difference becomes extremely important when one is trying to for example, understand a physical law, rather than the notation used to describe what is so far known of it.

But how can it be possible to understand the meaning of something not yet understood? The answer is that we let the parts of our new understanding of the meaning behind the behavior described by the symbols be defined by their relationships to the other parts. We construct self-defining whole pictures that allow us to fill in the details. This requires the use of the same modal logic faculties described above, and hence a hardware level feedback in the brain.

Feedback and Gain Control

All of the faculties listed above, that are prominent in people naturally immune to the DAM bug and not used in people with normal vulnerability are based in feedback at a hardware level in the brain. All engineers know that in any circumstance where they employ feedback, they must take care to control the gain of the circuit. This is the measure of how much the signal is amplified before it is reintroduced to the circuit’s input. Too little and it might as well not be there, but too much and it will quickly become a howl. The control must be just right.

This point is very important indeed. Existing understanding says that high dopamine gives rise to a state known as “alertness”, which can be identified by various behavioral traits that are deemed desirable in the DAM bug society. The best “alertness” is found in high dopamine people, and there is then a range of people of inferior “alertness” as the level of dopamine in their brains reduces.

Now the low dopamine people certainly have the faculties described above, and the evidence for feedback being involved is strong although circumstantial. So the low dopamine people must have their amplification precisely controlled! They are not at one of an infinite number of possible points on a line, they are at the one point where the feedback works! Therefore there is no range of anything healthy visible at all! There is a single point that gives rise to the faculties concerned, and a range of points where they are not present, and happen to be more or less far away.

Therefore despite being in a massive minority in modern societies, low dopamine people have healthy brains and are normal, and everyone else has been made unwell by the DAM bug parasitization of their society. Oh my!

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