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Dimension & Event Sorters & Classifiers - The Genesis of Artificial Conciousness & Abstract Machine Reasoning



Artificial Intelligence will remain stunted, and at best, a pale sort of intelligence until machines can have a degree of consciousness as to what they are doing.  The field of Artificial Intelligence is galloping forward in many different directions, doing amazing human-like things in the human domain, but it is still like monkeys typing Shakespeare. For a small discourse on the evolution of imperfect artificial intelligence, see the blog entry below called "Dawkins, Wasps, Artificial Intelligence, Evolution, Memorability and Artificial Consciousness".

Of course, one has to realize that not every application of Artificial Intelligence has to be perfect.  It can even be pseudo-AI if it does the job (Google searches are an example of kludged or pseudo AI as explained in the blog entry below as well.)  But I am talking here about pushing the boundaries of AI and making a case for Artificial Consciousness that can lead to abstract machine reasoning.

To accomplish these lofty goals, one needs to start with a practical framework and take the baby steps towards an Artificial Consciousness.  Therefore machines need to start collecting data and knowledge just for the sake of doing so. They must have event and state memory.  One could say that computer logs are a primordial event memory, in the form of action records. Indeed, academics like Professor Wil van der Aalst at the Technical University of Eindhoven in the Netherlands have made a science out of analyzing event logs. However their focus is to divine business processes from event logs.  They have made tools, some open source for doing so.  Their goal is to understand business processes using machine-generated data logs.   With just a little shift of focus, efforts such as those of van der Aalst could be adapted to do the analysis of the state of the computer at any given time.

State awareness is key to Artificial Consciousness. And the state transitions are events to be collected and analyzed as well.  The machine must have cognizance not only of it states but also of the actions that change states and drive state changes.

This process is akin to the development of a newborn baby. When it is born, it has just two main states, conscious and sleeping.  The sleeping state can be divided into the sleep stages - REM, etc and the state where the brain does neural net formation based on its sensory inputs and memory from the waking state.  The waking state initially has just two sub-states, comfort and discomfort.  The discomfort comes from hunger or the waste acids burning the baby skin from a full or wet diaper. The comfort comes from feeding or being cuddled.  All the while, the baby is hoovering up and collecting vast amounts of sensory inputs for processing while sleeping.

The baby's development of consciousness comes from state awareness. It begins with a classification of state and events.  Classification is demonstrated by the Sesame Street song where one of the things is not like the other -- a difference discriminator if you will:
 

Once you are able to discriminate difference, you are well on the way to having a classifier.  The concept of classification -- discriminating and sorting based on sameness and difference, the idea of collections of things and events becomes apparent. Although these are considered higher cognitive functions, many animals possess these capabilities.  My border collie used to sort his toys based on prime importance to him in holding his attention as playthings.

The formations of collections allows for the preliminary ability to abstract.  An abstraction can be as simple as choosing a parameter, property or function of everything in that set that all objects in that set exhibit.  In other words, the classification threshold can one of the abstract models of a thing common to everything in that set.

It's still a pretty dumb sort of abstraction, and the reasoning is limited to comparison, but it is a start.  Fortunately the operating systems of computers are fairly good at comparison and the sub-tools required for that, such as sorting and iteration through collections.  The computer does a decent job of collecting sets as well.

So the preliminary forms of artificial consciousness starts with data collection about internal self.  Then we advance to sorting and classifying the data.  From there we can get states.  Preliminary classification criteria becomes the abstract model of state awareness.  Once you have a good handle on the state, and an abstraction of that state, one can become aware of state change transitions or events.  It is just a short leap to start sorting and classifying events as well.  This adds power to predictive ability and is the first steps on the way to abstract, complex reasoning. Babies can do complex reasoning about state transitions at a very early age.  When the baby is negotiating say a bowel evacuation, there is a bit a stress that can be detected.  Then when the diaper fills, there is relief.  A full diaper is very enjoyable for the first thirty seconds as well, and this is reflected in the baby's emotional state.  Then when things begin to gel, so to speak, discomfort sets in and the baby reacts according.  One event drives possible three different reactions based on a timeline.  Time is the most important dimensions for prediction and reasoning.

The biggest cognitive asset to come out of a machine consciousness development protocol such as this, is that with more and more associations and abstractions comes the recognition of the dimension of the time.  States do not stay the same. They either transition due to external drivers or decay from one state to another.  These state changes or events allow for the cognition of the arrow of time.  The biggest step to autonomous reasoning will come from noticing and reacting to states and events as time goes by.


If the time dimension of states and events can be sorted and classified, then a machine will not only have a utile reasoning ability, but it will be able to do in with respect to time, and in real time. This will allow monitoring processes for things like self-driving cars and such.  The ability to abstract in the time dimension or domain allows for the reasoning ability to foresee consequences of action.  And in anyone's book that is both consciousness and intelligence -- and it won't matter whether it is artificial or not.

So what are the next steps to Artificial Consciousness? The machine must be able to discern its internal state through dimension and event sorters and classifiers.  Then it must be able to link up states on a time line uses probabilities for cause and effect and the interaction of events and states.  It will be a fairly primitive thing at first, but once you open that Pandora's Box, the evolution of artificial consciousness will be exponential in terms of progress.

Human consciousness has been explored by many throughout history, including pseudo-scientists. I have been fascinated by it ever since I once read that on an evolutionary scale, consciousness is nothing but a highly advanced tropism.  I know that many would disagree.

I once attended a meeting of Jung Society in Nassau, and paid $75 for the dubious privilege of attending.  A cheap Chinese buffet was included.  A psychologist and psycho-analyst was one of the speakers and he also happened to be a Catholic priest.  In his talk, he related the tale of how Carl Gustav Jung discovered the supposed human collective unconscious.  Jung was treating a patient with a severe mental disorder, and gave the patient a piece of paper and some crayons. The patient drew a rudimentary face on the page.  Gustav ruminated over the drawing and came to the conclusion that the patient had tapped in the collective unconscious and created a drawing of a Polynesian mask of some sort.  This was the germ of the idea of collective unconscious populated with instincts and archetypes, according to Jung.

At the appropriate time when it came to the question period, I gently pointed out that 99.99 percent of Freudian theory was debunked.  Brain physiology research had advanced to the point where we could identify substances such dopamines and other chemical receptors and inhibitors that were responsible for mood control and compulsive and unconscious ideations. I further pointed out that Jung's ideas had no scientific basis.  My observations and questions were about as welcome as strong bean flatulence in a crowded elevator.

One of the quotes on consciousness attributed to Jung was this: "There is no coming to consciousness without pain. People will do anything, no matter how absurd, in order to avoid facing their own Soul. One does not become enlightened by imagining figures of light, but by making the darkness conscious."

I would like to paraphrase that quote with scientific rigor. There is no coming to consciousness without sorting and classifying data about the internal state. People will believe anything, no matter how absurd to avoid facing the physio-mechanical nature of consciousness. One does not reach enlightened reasoning by imagining artificial constructs, but my making reasonable inferences using solid logic to achieve machine consciousness.  It's just the way it is, and I know that this view will be on the right side of history and human development.


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