Intuition Amplifiers 2

MAESTRO

MAESTRO

According to the last communication with baron it appears that my previous thread is most likely lost forever. Although it feels painful and somewhat unnatural to resurrect a thread I might have to do it. The thing is that I have received over 30 PMs and email messages from people who would like to continue the discussion. Although I have never tried it before I will now attempt to return “Ellen Ripley” back to life.
Ellen_ripley.jpg

I shall post brief synapses of our previous discussions and would expect other posters to remind us of their thoughts and comments expressed in the previous thread (Intuition Amplifiers 1)
It might take a while, but I believe that collectively we can restore the main body of the thread. I am asking you to be patient for a few days and refrain from posting new comments until we recover the heart of our previous discussion.
I will first start posting bits of material that I have saved and then I will repost some definitions that I have proposed in the previous (and sadly lost) thread. Then I shall present the layout of what is coming ahead. Please briefly remind us of your previously posted comments and statements. Try to be initially concise in expressing your points of view. Remember, there will be lots of time to expand on your thoughts.
Let’s try it, shall we?

Cheers,

MAESTRO
 
In his 1956 ground-breaking book “An Introduction to Cybernetics” William Ross Ashby has presented to us the law of Requisite Variety. What this law simply states is that for any system to be stable the number of distinct states (variety) that its control mechanism is capable of producing must be greater or equal to the total number of states (variety) of the system itself. In other words, if a system operates in the environment that causes it to assume certain number of states the system’s control mechanism must be “smart enough” to recognize all of those states and react accordingly. If the system operates in the rapidly changing, complex environment the control mechanism must also have an ability to quickly increase its variety (i.e. to learn) in order to maintain the system’s stability. This necessity, of course, underpins the “survival of the fittest” principle that has always been the corner stone of the modern evolution theory. Indeed, the very survival of us as humans and our dominant position in today’s world should be certainly attributed to our internal control mechanism (human brain) and its ability to increase our “variety” in synch with the constantly increasing “variety” of the environment. With our remarkably effective brain structure and its immeasurably superior reasoning mechanisms, we are unmatched in our abilities to process a myriad of interconnected facts and to rapidly make logical decisions. It is our brain’s capacity to use logic made us the dominant form of life on the planet. But this “superiority” comes with the price.
The way we increase our “variety” is mostly based on our social interactions. Right from our birthday we interact with the outside world by primarily using our relationships with other people. As highly social animals humans structure their very existence around bonds, dependencies and social ties with other humans and their social groups. These relationships first and foremost are designed to enable our “quick” access to much greater “variety” than one individual could ever possess – the “collective variety”. One of the main tools that we, humans, have developed to obtain this “collective variety” is the information technology. From the ancient Persian messengers, to homing pigeons, to telegraph and radio and, finally, to the modern Internet our progress in the area of communication technology and information exchange significantly outpaced the progress in any other area of human evolution.
 
Because information technology evolves much faster than we can, the gap between our data comprehension capabilities and constantly increasing flow of facts is exponentially widening. More and more often we find ourselves in the situation where we just don’t have enough time to use our logic and make the “If – Then” type of decisions using our neo-cortex, frontal and parietal lobes. Ironically, in order to handle this overwhelming flood of changes, decisions, and choices we are increasingly forced to fall back on our reflexes, instincts, intuition and other subliminal mental faculties similar to ones of the lower animals. Our well-developed neo-cortex is increasingly failing to adequately deal with the complexity and richness (“variety”) of the outside environment. Unlike the other animals that have evolved without dramatically increasing “variety” of their environments, we have created our own comprehension deficits by synthesizing an infinitely more complex world. As a consequence, our artificially created “variety” forces us to look for other viable alternatives to keep pace with the avalanche of information we have created. In many aspects of our lives we have no other choice but to substitute the time-consuming, thoroughly logical decision making with a more reflex, “primitive”, intuitive type of reacting to the changes that our communication driven world throws at us.
 
When we drive a car, fly a plane or trade markets our ability to succeed strictly depends on how fast and accurate we make crucial decisions. Highly dynamic, rapidly evolving situations (especially if they are surrounded by a high degree of uncertainty) demand us to be nimble and not to rely on the time-demanding and sometimes misleading logical type of decision making. When our wellbeing depends on split-millisecond decisions the instincts, intuition, experience, anticipation and reflexes are our only hope to survive. Unfortunately, we were so focused on creating better, faster, wider channels for information delivery and its logical processing that we have not paid much attention to creating equally sophisticated methods and devices to improve our cerebellum based decision making abilities. Our available aids to enhance our perception capabilities, intuition and subliminal decision making skills are disproportionally dismal compared to the mountain of gadgets we created to distribute and consume information.
 
It takes a human about 250 milliseconds to blink. It takes approximately 50 microseconds for an electronic exchange computer to fully complete a financial transaction. There are hundreds of electronic exchanges world-wide that simultaneously run thousands upon thousands of “transaction matching” computers. So, by the time you blink, there could be billions of dollars that exchanged hands and millions of financial securities bought and sold on the world’s electronic markets. Today’s exchange runners are fiber-optic cables and today’s “Gordon Gekkos” are computer algorithms — math-based programs mining markets from New York to Hong Kong 24 hours a day.
 
Second to military organizations financial industry is the headhunting top for math and physics Ph.Ds. Launching what some have called a “technological arms race” the financial industry has become the driving force for the most advanced computers, artificial intelligence based programs and communication infrastructure in the world. To keep up with the escalation of data delivery and its processing demands we devote mind boggling resources to our information systems infrastructure.
 
We absolutely must have an ability to override our “automatic pilots” and switch to the “manual control” when we need to “land our malfunctioned planes” safely. We must develop an alternative set of tools that are independent of our computer algorithms and are efficient enough to enable us to comprehend, assess and timely correct our machine’s “misbehaviors”. We desperately need to be as fast as our computers and “fight back” for our dominant role in our artificially created, exponentially complex environment. We, ourselves have created the new “species” on this planet and now we are passively observing them slowly but surely pushing us out of what used to be our exclusive field of expertise – decision making.
 
It is good to “delegate” and free up our minds of routine mental chores such as number crunching, data storage, search and sorting of information etc. It is also good to have auto-pilots, self-parking cars and buy/sell algorithms to trade markets providing that we are still in a position to take over when needed and to be as efficient as our “robots” in performing those tasks. Unfortunately, most of us have resigned to the fact that our brains are incapable of competing with the machines we have created. In this thread I will try to prove the opposite.
 
There are, of course other examples of explicit and vivid differences between humans and computers. An average human would experience tremendous difficulties when trying to multiply 2,345,321,098,213,469 by 323,425,580,982 just using his/her mental calculating abilities and of course modern computers can calculate the answer almost immediately. However, humans can easily tell when another person is in a “bad mood” by instantly reading that person’s very subtle facial expressions or their body language. On another hand, distinguishing between happy and angry expressions on your face would certainly create an overwhelming challenge to even the most sophisticated computers. It is interesting that the very reason why humans have established such a great bond with dogs is because dogs unlike the majority of other animals have developed an ability to recognize human facial expressions and react to them accordingly.
 
An average person has around 120,000 strands of hair on their head. Imagine that the length of each individual strand is measured and then presented as a list of numbers separated by commas. If were to show this list to an average human and ask her to determine the length of the longest hair on the list we would find out that it takes good 5 to 10 minutes for that person to come up with the answer. However, if we feed this list of numbers to a computer and use its simple number sorting algorithm we would get the right answer in less than a second. Clear computer advantage, isn’t it? But let’s slightly modify the challenge. Let’s now ask a human and a computer to find and cut the longest hair on a person’s head while this person is sitting in the barber’s chair and leisurely talking to other people in the shop. This is what your barber effortlessly does in a split second thousands times a day. This also is a virtually impossible challenge for a modern computer even after spending years of designing, programming, debugging, adjusting and (hopefully) safely testing what would be an enormously complex algorithm. The task is even more gargantuan if it needs to be performed in a great variety of its modifications thus achieving different hair styles. Who is the winner now?
 
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