Learnt functions are activities - ‘programs’ to use the analogy – that have been deduced – worked out as it were - by observation of the world about us. In other words, all learnt function is reliant on perceptions. Most of this deduction is achieved by pattern matching.
There are two sorts of learned function:
- The executable function - those we can directly use - execute
- The predictive function - those that enable us to reason and make decisions. Thus we can work out the consequences of doing something or alternatively predict what might happen next.
Executable functions are those we can use directly. They include speaking and writing, for example, riding bicycles, or driving a car. All these systems are ‘man-made’, for example, language and the use of language when we speak is a man made system. The rules of grammar and language are also man made.
Many of these learnt functions, over time become almost automatic functions, in that we do not have to consciously think too hard whilst we execute them
A predictive model is a model of how we think the world or the universe works. It is a vast vast “simulation” system of the universe, our idea about how all the activities interact, how they behave, how we can use them.
It is of course only a model. We build it up by using perceptions to produce a system model in our minds. It cannot be ‘reality’ because we only have so many observations to go on, but in time we find all sorts of functions - we get to know the sun sets, the wind blows, birds fly, grass grows, plants may flower, babies are born, we all die, we all get old, puppies chew, babies cry, and water flows.
Most predictive models are based on the idea that for any one event, then one or more activities are likely to follow in sequence or in parallel. Thus, for example, for anyone watching me and not knowing the instructions, they might see that if The Post is delivered [event], then what will happen next is that I will:
- Take the Post key
- Go to the post box
- Open the post box
- Take out the post
- Lock the post box
- Come back and put the post on the table
The sequence of action is so frequent and regular in its activities, I think I can justifiably call this a system.
Why do we need predictive models?
I might have seemed a little flippant in my treatment of predictive models, but they are extremely important in the present scheme of things. Since we haven’t asked the spiritual world what the systems really are, the only means we have of running our everyday lives is to use these rather inadequate models.
Why do we need them? Because without this understanding we would not survive very long and as in days gone by we would live in fear wondering about how to react to each event.
Some sorts of system are still predictive, but less easily analysed because we may not see all the actions that take place. Here we may have an event that triggers a whole host of largely invisible activities, but we may see an outcome.
We then perhaps think of these as ‘rules of thumb’ – heuristical systems that give a set of possible inputs and a set of possible outputs but without any clear idea of why this happens.
For example, if I feed my tomato plants with Food X in Spring, they will grow. Why? – Well the processes may be unknown, but the cause and effect seems to be a regular pattern so worth pursuing.
Much of our ‘science’ is based on this form of model at the moment – it is not very satisfactory as a knowledge base, but I suppose, it is better than nothing. It is not better than nothing when scientists do not recognise it as such.
It is worth pointing out that this form of building models is highly unsatisfactory, no computer systems analyst would ever accept this in building computer systems, but much science appears to be based on experimental work and repeatable results, so this form of approximation tends to be the norm.
It is actually wrong however for any scientist to claim that the results of this form of observation is scientific.
In days gone by, much of the superstition that rather dogged our existence was obtained in this way – repeated observation of some phenomena with defined inputs and regular outcomes. Despite all claims by scientists to the contrary we haven’t moved much beyond this state, we just have different superstitions and continue to be struck dumb every time patterns suddenly change.
The posh word for such models in psychology is a ‘heuristical model’.
In computing we tended to call them a waste of time.
Some example heuristic models
Most heuristic based models we develop are based on observable causes and effects, without any knowledge of the intervening activities. There has been a repeating pattern, so we assume it is a rule ……. For example here are some silly sayings that demonstrate the heuristical model at work:
- Find a penny pick it up, all the day you’ll have good luck
- A stitch in time saves nine [this isn’t a bad heuristical model]
- Early to bed, early to rise, makes a man healthy wealthy and wise
- Red sky at night, shepherd’s delight; red sky in the morning, shepherd’s warning
- A fool and his money are soon parteying
- Only one guy is worth your tears, and the guy that is won’t make you cry
- A wise girl kisses but doesn't love, listens but doesn't believe, and leaves before she is left
- A wet cat never flies backwards [this has proved remarkably sound heuristically – it seems to work for dry cats as well].
And on this page we have some examples of men of reason and power - clever men - using their inductive reasoning processes and a bit of heuristical knowledge, how comforting that they are in charge ………..
"I have traveled the length and breadth of this country and talked with the best people, and I can assure you that data processing is a fad that won't last out the year."
-- The editor in charge of business books for Prentice Hall, 1957
"There is no reason anyone would want a computer in their home."
-- Ken Olson, president, chairman and founder of Digital Equipment Corp., 1977
"The wireless music box has no imaginable commercial value. Who would pay for a message sent to nobody in particular?"
-- David Sarnoff's associates in response to his urgings for investment in the radio in the 1920s.
"This 'telephone' has too many shortcomings to be seriously considered as a means of communication. The device is inherently of no value to us."
-- Western Union internal memo, 1876.
"Heavier-than-air flying machines are impossible."
-- Lord Kelvin, president, Royal Society, 1895.
"Drill for oil? You mean drill into the ground to try and find oil? You're crazy."
-- Drillers who Edwin L. Drake tried to enlist to his project to drill for oil in 1859.
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- Alain Danielou - While the Gods Play - 01 The Experimental Method (Vaisheshika) #022542
- Amiel, Henri - On inspiration #005150
- Arnold-Forster, Mary - Where do dreams come from? #001996
- Babbage, Charles - The Ninth Bridgewater Treatise #004028
- Book of Enoch-42 #004852
- Crowley, Aleister - from Yoga for Yahoos #006439
- Custance, John - Wisdom, Madness and Folly - On the depressive phase #005169
- Damasio, Professor Antonio - David and learning #006058
- Damasio, Professor Antonio - Systems of communication and Inner speech #014822
- Descartes, Rene - Behavioural function #002950
- Descartes, Rene - On appetites and emotions #002948
- Einstein, Albert - The Laws of Nature #002428
- Foer, Joshua - National Geographic - Remember this #015609
- Fraulein O #006036
- Goethe - Faust Part 1 #010831
- Huxley, Aldous - Misc. Quote - The complexity of character #015442
- Koestler, Arthur - Janus - Creative thought #002684
- Koestler, Arthur - Janus - Learnt function #002677
- Koestler, Arthur - Janus - The unreliability of memory #002683
- Krishnamurti - The Network of Thought - You, the ego… the me is just memory #013522
- Lilly, John - LSD and self destructive programs #000981
- Meister Eckhart - Selected writings - Question all beliefs #002688
- Nietzsche - On the Genealogy of Morals - Pain is the most powerful aid to mnemonics #003808
- Oliver Sacks - Victor the Wild Boy and what he learnt #006072
- Ramachandran, Dr V S - The distortion of perceptions to fit belief systems #013531
- Sahib, Bhai #004936
- Slow oscillations orchestrating fast oscillations and memory consolidation #021363
- Steiner, Rudolf - Nature spirits - Thoughts #013755
- Sybil, Vicky, Marian and Peggy Lou #006039
- Tennyson, Alfred Lord - In Memoriam A H H - The baby new to earth and sky #013883
- Tennyson, Alfred Lord - In Memoriam A H H - Who loves not Knowledge? #013878
- Thoreau, Henry D - Walden - The Laws of Nature #001846
- Watson, Lyall - On exorcism #001008
- Whately Carington - The learnt function of spiders #014546