Creativity arises naturally from abstraction and similarity, features of Mental Construction, a description of neural processing on perception and thinking.
We use many words in various contexts attempting to capture aspects of novelty in thinking: intuition, leap of faith, insight, …
Creativity is not restricted to Einstein, Picasso, and similar figures of towering creations. It occurs in the life of everyone. It’s just that most of us perform our creativity on events in our life and our sphere, unnoticed by all but our friends and family.
The Encyclopedia Britannica defines creativity as “the ability to make or otherwise bring into existence something new, whether a new solution to a problem, a new method or device, or a new artistic object or form.”
Bringing “something new” is beyond the power of deductive logic. Although it can guarantee its conclusions, they are constrained to the content inherent in the premises. Induction does bring “something new” in when it’s used to generalize from specific cases to a general theory. Counterbalancing that power, we all know the dangers of jumping to conclusions.
If you’re thinking the scientific method produces new truths. I won’t deny it, but let me point out the scientific method is not strictly deduction. The hypothesis tested—and used as a premise in logical deduction—has been creatively posited. As Jacques Hadamard noted in the Creativity in , outside of logic. It’s beyond logic.
Mechanism of Creativity
Searching through the literature for explanations of the actual act of creativity, phrases like something arises from the preconscious or an ahah of insight occurs. Mental Construction arranges four operations that lead to creative thought.
Neurons in the brain transfer their input forward if it surmounts the Almost Gate, the sum of their input exceed the neuron’s threshold—and it doesn’t matter which of the average 10 thousand inputs are on, just that the aggregate is greater than the threshold. This means that raw data is eliminated from the information that flows out the axon. It is an abstraction, a generalization with less detail.
Sense data gets routed to specific parts of the brain to be enhanced. Similar data is seen repeatedly. Hebb’s Law of Neural Learning explains that the similar firing of sets of neurons induces them to fire again on similar sets of inputs. The pattern, the similar set of inputs, must surmount an Almost Gate to be passed forward. That’s how we each develop sensory and semantic (meaning) maps in our brains.
99.9% of all cortex neurons received their data from other cortical neurons. Only 0.1% of all cortical neurons connect to either sensory cells or motor cells. Each passing of a pattern in the next inward adds additional imprecision upon the transference of information. If there is 99% fidelity in pattern transmission from step to step in processing, after 50 steps (a low estimate in the number of handoffs of information) the match is down to 60%. In Mental Construction concepts, the amount of external reality that is used in deeper Almost Gate calculations decreases at each step, implying the Almost Gate can be surmounted more and more by the amount of remembered information that is in the pattern input.
After sensory data goes through its processing (extraction, identification, abstraction, categorization—an interactive process with one’s memory and cognitive resources—it gets integrated with other sensory input. At each step away from raw data, the sensory data
As discussed, the Almost Gate has an idiosyncratic threshold, so that each person triggers information flow downstream when it has a different fidelity. So, although we each perceive through neural thresholds, different Almost Gates result in somewhat different perceptions.
In the Creativity Dimension figure, people with very high Almost Gates, very high neural thresholds, require almost everything to be aligned before they will declare a match. On the opposite end, people with quite low Almost Gates allow more sway in their thinking. They will see relationships when there is a good bit of differences between things. I’m being vague, using the word ‘things’ because the Almost Gate operates not just on sensory data, but on categories, concepts, memories, and theories.
Goals drive our thinking. They arise from our bodies and our emotions, not from our conscious brain. They come from our limbic system which evolved many million years ago and in our particular bodies developed in our early childhood, ages 2 to 5 or 6. As we grow older, we extend in our cognitive minds, our needs and goals according to our success in satisfying them. No longer are our goals to be safe, have enough food, and an attractive partner. They become get a good job in a field that we flourish in, which will allow us to buy a house in a good neighborhood, be able to pay our bills, and satisfy our mate.
That’s a very casual gloss, so let me delve a little deeper.
There’s a specific term in computer science which is useful here. From Dictionary.com,
Real-time. of or relating to applications in which the computer must respond as rapidly as required by the user or necessitated by the process being controlled.
Many goals are immediate or real-time. They must be met soon after they arise. Life-and-death situations demand immediate action, but others exist that are not so dire or could be avoided. Immediate goals exist in all sports, where all other considerations are shunted far into the background, so that all energies (attention, thought, and actions) can be devoted to winning the game, not falling from a mountain side, and executing a perfect figure 8. A real-time goal is satisfaction of hunger and thirst. Depending on one’s age and situation, the desire for sex can be either immediate or long-term.
No matter the immediate goal, typically it must be satisfied within the situation that we are currently experiencing.
Delayed Gratification and Not Yet Available
Although often mentioned as an alternative choice to immediate goals, that is not the salient feature. Delayed goals are typically delayed because they cannot be satisfied in the person’s current situation, not because delay is preferable.
Inductive Path to Goal Satisfaction
The deductive path is the logical way. You want to make a lot of money, so you target an occupation that has lots of rich people in it.
Everyone always talks about the logical way to achieve one’s goals, so I’ll take that path for granted. It’s well discussed. Let’s talk about the inductive path to goal satisfaction.
If two situations have many points in congruence, not mattering greatly what the points are, then something that worked successfully on the first situation should be tried on the second situation. Earlier in section the example of deciding how to induction affected hot to react to the stock market in 2009 was discussed. Let’s discuss a more direct personal situation—your new driver has asked to borrow your car for an evening at her friend’s house.
There are logical deductions you can make. Your child drove well in the times when you trained her. So you may conclude that she will drive safely tonight. Of course, you haven’t seen her in all driving situations she may faced with, so there is an inductive component to your logic, but that probabilistic constraint always exists on all logical calculations.
A is to B as C is to D. Don’t just through your hands into the air. Read through this description.
In your memory, in situation A (for instance, you and your best friend hanging out) seems to lead to result B (for instance, getting pizza at the eatery and talking about plans for the weekend), especially if you preform action z (for instance, offer to pay for a large drink that you both can share).
Now, situation C has come up (for instance, a new school acquaintance and you are walking by the mall). You want to hang out at the mall. You suggest that you will get a large drink so you can share. After you buy the drink, your new acquaintance drinks almost all of it and walks away, leaving you alone at the table.
You tell yourself, next time you won’t be so naive. There’s reasoning there but it’s not logical. It’s pattern-fitting.
Analog Decision-Making Example
Flushing the example and explanation out somewhat further. Consider you are going to a magnet school, across the city where no one knows you and you don’t know anyone. On the first day who do you take actions to befriend? You only have your first impressions to guide you. You know nothing about what they have actually done, only how they look and how they carry themselves. Yet you make your decisions. Some turn out to be good friends, others snakes in the grass. You don’t base your decisions on logic, but on analogy. You use superficial similarities of new potential friends to actual friends and acquaintances of whom you know the relationship between their presentation and their actuality. You base your decisions on similarities, not on concrete logical relationships.
In fact, while I was describing this you might have been thinking, “I didn’t do any logical deductions. I just felt that the one guy was a jerk and that girl seemed nice. No more thought than that.”
We use the word ‘thought’ with many nuances in casual discussions. When you make the friend decision as above, some many not call it thought because it didn’t bubble up to words in a logical order. They have an unwitting bias which demands that thinking be in words and logical relationships. Anything else is not thinking. It is illogical, which has the stink of loony or crazy. But making decisions based on similarities is not loony or crazy although it is illogical. Illogical, in that, logic does not lead to the conclusion.
Conclusions are driven on similarities of appearance, timing of occurrence, emotional content, particular experience, and one’s genetic expression. Not only do these conclusions deserve equal standing with logical conclusions, they have a feature that logical conclusions can’t reach. Inductive conclusions are creative. They go beyond the knowledge that the past and the current situation prove. That’s a garden that logic can’t reach without induction’s help.
You have seen the main aspects of natural, neural operations on how we think and the many ways its consequences are weaved into our perceptions, beliefs, and mental structures.
After reading these pages, you need a break from intricate reasoning—whether it’s logical or based on patterns.
Stop back later. I am adding posts which go beyond the main argument outlined in the Table of Contents. They cover other aspects of thinking that lie in psychology, philosophy, linguistics, sociology, and neuroscience.