Bending, blending and breaking biases

It’s a paradox that AI developers are striving to make AI unbiased, when the key to human intelligence and creativity lies right there, in our biases. In this blog post I will show you why biases are so important for creative exploration and learning.

In this series on human and artificial creativity I use a common definition of creativity as novelty that works. In the previous blog post, The stochastic of divergent thinking, we explored properties of the stochastic process of divergent thinking, the first stage of a creative process where candidates of novelties are suggested. In this blog post I will turn to how our biases put constraints on divergent thinking, but also how we use biases to evaluate the usefulness of a divergent thought. Does it work? Is it meaningful? With regard to the potential of artificial creativity, the aspects of human creativity discussed in this blog post will most likely be a much greater challenge to the artificial implementation of creativity than the stochastic processes discussed in the previous blog post. Nevertheless, we need to delve into the role of biases in human creativity before we can understand whether human creativity can be replicated or simulated in computers.

In order to be creative we have to deal with the constraints of biases, and the title of this blog post is inspired by the findings of Eagleman and Brandt who found that most creative acts can be categorized into one of three main ways of dealing with biases. 

Either you bend them, or you blend them, or you break them! 

But before we turn to the importance of biases in the creative process, I will focus a bit on how our biases affect both our perception and our attention. When I use the term ‘bias’ here, I have a wide interpretation in mind, representing some cognitive structure, either inherent or learned. I will occasionally also use other terms used in psychology, neuroscience or statistics, like, ‘reference frame’, ‘belief’, ‘prior’ and ‘intrinsic model’. Common to all is that they represent some subjective structure of knowledge or belief that we already possess. It might be anything from knowing how to discern apples from pears, to more abstract opinions about the existence of free will or God. 


Biases are attention filters

The human brain is both conservative and novelty seeking. It is well known from psychology that we are biased towards trying to confirm what we believe to be true, our opinions and prejudices. This is known as confirmation bias. However, this is, luckily, balanced by an urge to seek novelty. The salience hypothesis in psychology addresses the question of what guides our attention, and it states that our attention tends to seek novelties or things that “stick out” in our environment. Our senses are receiving a tremendous amount of information every second as we are awake, and somehow the brain has to filter out most of this information as it seeks some attention point. It makes sense to think that we should attend to things that change or differ from some background. 

Surely, this is a good thing, for instance, if we drive along the street and a cat suddenly jumps into the road. The cat, representing a sudden change or surprise, attracts our immediate attention and gives us a chance to hit the breaks. However, a bird flying by in front of the car is less likely to give the same reaction, unless you are an ornithologist, perhaps. This example indicates that our attention is not only drawn towards novelty or surprise. This was demonstrated in study by Henderson et al.. They showed in experiments that visual attention is, in fact, also drawn towards meaning, and not surprise or novelty alone. This is contrary to the salience hypothesis, which has been the dominant view in later years. Human attention is thus guided by top-down intrinsic bias, an inner motivation, guided by meaning, interest, values or feelings. We might say that we are drawn towards surprises that are meaningful to us. Without this top-down evaluation and filtering of novelty, we would be swamped in all the unexplainable noise that surrounds us everywhere! Hence, we are born to be creative in the way we naturally seek novelties that work!


Biases and prediction errors

Besides serving as filters for attention, biases may have an even more direct influence on perception, for instance, on what we see or hear. A recently developed theory on human cognition is the theory of predictive coding stating that we all, in our daily lives, learn about and adapt to the environment by making predictions based on internal, cognitive models. We sense the world through our beliefs, and they are either retained or adjusted according to prediction errors. These errors are the differences between what we observe and our prior expectations based on the intrinsic models of our surroundings. So, we may say that we have internal, cognitive models of how things around us are expected to be and how they are predicted to change. In the extreme we could say that what we actually perceive are prediction errors! Hence, the intrinsic models, or biases, therefore also influence how we perceive the world. The act of learning is an ongoing Bayesian process of model updates in light of our prediction errors. It is therefore crucial for creative learning that we dare and are allowed to make errors to learn from!

Thus, biases and internal models of our surroundings are important mental structures, essential for survival and well-being. Throughout life we learn to categorize sensory inputs and ideas to predict future outcomes in a random world. We build or adapt opinions, about values, interests, culture and ethical standards, all being mental reference frames helping us make decisions and bring meaning to our lives. Thus, through learning we build order in chaos, a hierarchical structure of biases, of boxes, to put life into. Some boxes are wide and big, like ‘beauty’ or ‘symmetry’, others are narrow and perhaps contained in others, like ‘carrot’, and ‘vegetable’. Many boxes we learn or adopt from others, some we creatively discover ourselves, and some we are even born into life with. 


Biases limiting divergent thinking

As discussed in the previous blog post, The stochastics of divergent thinking, the associative thought-process can statistically be compared to a non-stationary stochastic process, where the transition probabilities over the flexible state space of thought change over time and with context. It is very plausible to assume that the transition probabilities, defining which thoughts are more likely to be associated together, depend on our biases; our learned structures of interests, values, opinions, prejudices and so forth. Hence, if we have strong biases, they are also likely to put limits to the process of divergent thinking, making it less likely to generate atypical ideas. If a person has very strong opinions and beliefs, and perhaps scores low on the psycho-analytic trait openness to new experience (Big Five inventory), he or she may be very limited with regard to divergent thinking. 

During our lifetime we are constantly expanding our level of knowledge, building order in chaos, a complex bias structure, which may become increasingly rigid and non-flexible. This may put limits to creativity and may explain why children seem to be more open to new ideas and be more creative than elderly people. Ronald A. Havens summarizes the insightful thinking of the famous psychotherapist Milton Erickson about this paradox of learning limiting new learning this way:

At first the ordinary person’s mind is relatively unstructured, objective, flexible and open to new learnings. Over time, however, it naturally becomes increasingly rigid, biased, idiosyncratic, and unable to accept perceptions, learnings, or responses that cannot be accommodated by its previously adopted structure.

And he continues:

Eventually the entire conscious awareness of the individual may become restrictively governed or dictated by the very structure that originally developed to allow an increased freedom of response.

In his book On creativity David Bohm describes this as self-sustained confusion that can arise when a person’s mental frames have become so rigid and structured that any divergent thoughts challenging this mental structure become conflicting and painful. 

Sometimes this conflict is an inner conflict, but sadly the conflict may also be induced from the environment. The most popular TED-talk is the hilarious talk by Sir Ken Robinson with the slightly provocative title: “Do schools kill creativity?” Robinson makes a convincing argument that we are all born creative, but school has the unfortunate effect of making us suppress this inborn skill in the way our educational system is dominated by supervision, how it rewards conformity and punishes divergent thinking. Being “wrong” is not accepted, and the result seems to be to surrender to self-sustained confusion. This is sad considering that prediction errors are such a rich source to learning.


Biases and creativity.

I will now briefly point back to the previous blog post where a two step procedure for data simulation using Markov Chain Monte Carlo methods was used to exemplify the creative process. A dependent chain of values is iteratively generated from some target probability distribution through the two steps:

  1. A new candidate value, typically depending on the current, is drawn from a proposal distribution (a random step). 
  2. The candidate is accepted or rejected as a new value of the chain in light of the target distribution (an evaluation step).
Inside or outside the box?

In the previous blog post we focused on the relevance of step 1 (divergent thinking) as part of creative processes, but for a divergent thought to be accepted as creative it has to be evaluated with regard to its usefulness. Every new thought aspiring to be deemed creative must be evaluated with regard to its usefulness within some reference frame or bias structure. It is common to use the phrase thinking outside the box to describe the process of coming up with new and unconventional thoughts that may lead to creative ideas, artwork or scientific discoveries. However, I believe this is turning creativity inside-out, literally. Creativity is always to think inside some box, because without a box (a bias, or a frame of reference) the usefulness of a novel thought cannot be evaluated! 

Our biases and reference frames may statistically be seen as priors in a Bayesian belief update process. Given our biases and mental models about how the world is, we evaluate the likelihood of new observations. If new observations seem trustworthy, but in conflict with our beliefs, we may “choose” to change our beliefs. On the other hand, if biases are strong and data are ambiguous, we may stick to our beliefs. This balance between the likelihood of new observations and our prior beliefs is expressed by Bayes rule, which we quite heuristically can write like this:

Posterior (belief) ∝ Prior (belief) ᐧ Likelihood (new data | belief)

Where the symbol “∝” means “proportional to”. In an ongoing learning process, prior beliefs are updated (or not) into posterior beliefs in light of new observations. The posterior belief may later serve as a new prior belief as part of continued learning. However, if Bayes’ rule was the only way our beliefs could change, we would not be very creative! Any novel idea would receive a low likelihood given our biases, and the result would be to be stuck in our priors. The most radical way to be creative is to change our prior beliefs, to transform our biases.

Hence, creativity is most about challenging our old boxes, and to bend, blend or break our hierarchical bias structure and reference frames. A divergent thought may be rejected as being creative according to one reference frame, but can, in fact, be accepted within a wider or transformed reference frame. After reflecting upon and studying the creative process for a long time, and being particularly inspired by Bohm’s stages of imaginative and rational insight and fancy, I have come to a conclusion regarding the very essence of creativity. 

The true act of creativity is the restructuring of intrinsic structures, biases or reference frames,  with the purpose of bringing meaning to novelty. 

Hence, the actual painting, a sculpture, a new music play or even a new scientific theory are not creative in themselves, and neither is the craftsmanship or the deductive reasoning that produced the sculpture or the new theoretical lemmas. Such manifestations of the creative insight into something observable is merely a matter of skillful production or deduction (Bohm’s fancy). It is the imaginative and new insight of a new order, a new concept, or a new reference frame, which is the true leap of creativity. However, both insight and fancy are necessary stages in a creative process in the way they work interchangeably and stimulate one another, according to Bohm. This is also well known from design thinking principles. On the other hand, one may question whether a person, or a computer (as we will return to in the next blog post) is creative in case he/she/it is only involved in the deductive reasoning step of the process. 

David Bohm uses the story of Helen Keller to illustrate the creative transformation or discovery of structure or order in chaos happening in the stage of insight. Helen turned deaf and blind after catching a fever when she was less than two years old. Without language she spent her first years more or less isolated from the outer world until her parents hired a private teacher, Anne Sullivan. Sullivan came to Helen’s rescue and managed to reach into her mind by clever conduct and patience. She did so by exposing Helen over and over again to the substance of water under different conditions, like ice, liquid water and steam, each time writing «water» in the palm of Helen’s hand. At first the sensory input signals Helen received must have felt rather chaotic, but in a moment of sudden awakening, Helen realized that all sensations could be classified together, everything being water. Bohm points to Helen’s sudden realization of a higher order structure, the concept of water, as an example of high level creativity. Although Sullivan tried to help her come to this realization, the giant leap of discovering order in chaos had to be made by Helen herself. 

In the following we will look closer into how biases are used and transformed in different types of creative processes. This will make it easier to discuss the potentials of artificial creativity later.


Supervision (Bottom-up processing)

Supervised learning may serve as a baseline with which to compare creative processes. If, for instance, a kid or a student acquires all knowledge and mental structures from external sources, like from a parent or a teacher, in an entirely bottom-up type learning process, we may refer to the learning process as being supervised. Bottom-up learning means that information flows from input perceptions from our senses to form knowledge, but in a non-creative way. In the extreme, all order, structures and biases are directly transferred from a supervisor to the learner.. Without reflection or critical thinking this is purely an information transfer process. A bottom-up learner would always follow instructions and never raise a critical question to the knowledge structures. Hence, pure bottom-up learning does not nurture creativity. 


Imagination (Top-down processing)

Imagination is a requirement for all types of creativity, and especially for Bohm’s fancy stage of a creative process. Neurologically it is a top-down process, where the top level biases are fed back to the sensory cortices to either alter factual perception of the world, or to (re)play 100% imaginative experiences, like we do in dreams. If I ask you to close your eyes and imagine the face of a close relative, then recent research supports the notion that you are in fact running your neural system backwards, from your higher order structures defining your relative, down to the mid-layers of your visual cortex area to create a mental picture of the face of your relative. Hence,  imagination is reverse application of cognitive biases by a top-down information flow. This opens the ability for humans to imagine possible futures or to perform imagined experiments, like Einstein´s «Gedankenexperimenten», which is an important part of Bohm´s fancy. Neurological studies support this. For instance, Kounios and Beeman found through EEG studies that people, who through tests appeared to be more imaginative than others, had higher resting state activity in the visual cortex.

 As mentioned above, the title of this blog post is inspired by the findings of Eagleman and Brandt who observed that most acts of creativity may be described as a result of three different ways of challenging old biases, namely by “bending”, “blending” or “breaking”.



Relatively novel and useful creations may come about as small adjustments to already accepted ideas, theories or structures. A small change to established ideas is typically easy to suggest and readily acknowledged. Probably, most published research can be described as “bending” of previous work, making incremental steps towards a more complete knowledge structure of a given field within an accepted paradigm. Also in art, bending is common, but whenever the work of a scientist or the creation of an artist is regarded as highly creative, bending is probably not the type of creativity involved. In terms of Bohm’s insight and fancy, I would characterize bending as primarily applying imaginative and rational fancy to already accepted bias structures and hence, the level of creativity is low, and the manifestations can be characterized as variations of a common theme.



“Blending” is a good characterization of creativity that is a result of applying previously learned structures to new areas. In this way order is extended by recognizing that old familiar structures may be “blended” into the new and unexplored variability. Returning to the story of Helen Keller, in addition to having a sudden insight about water, she also had an immediate realization of concepts as a general structure which could be applied to (or blended into) other experiences beyond water. This learned structure opened up endless possibilities for exploring new experiences for Helen through blending.

Blending is a powerful tool for learning in general, not only for creativity. In supervised learning, the use of metaphors has been used for millennia to help students understand and learn new concepts. The Biblical parables are ancient examples of such, and so is Plato’s allegory of the cave. Similarly blending may help the brain to see new order as part of a self-supervised creative process.



The son of Pablo Picasso once said about his father that he had the habit of breaking everything, only to rebuild it in a novel and creative way. This is a perfect example of the last type of creativity defined by Eagleman and Brandt, namely «breaking», which is a kind of self-supervised revision of existing structures.This is likely the most challenging type of creativity in two ways. 

Firstly, as humans we tend to prefer to confirm old structures (confirmation bias). Breaking established order is for most people experienced as a stressful experience since the sense of stability is reduced or even destroyed. The scientist or the artist who questions structure must endure the emotional distress of the increased disorder and chaos that occurs before a new order is found. David Bohm writes about the self-sustained confusion maintained by those who cannot bear the distress of breaking old reference frames. This confusion may be sustained even if the old, and perhaps dear, biases clearly violate experience and perceptions. Rather than going through the pain of breaking and rebuilding biases, a person may confuse her-/himself by pointing to increasingly improbable explanations and exceptions. This may be a problem both in society at large, but even so in science. Scientists who have devoted their entire career within a scientific theory or paradigm may emotionally cling to the old biases and structures, rather than accepting that the contradictions between theory and data indicate the need of breaking and rebuilding theories.

“[on originality]…, he must be able to learn something new, even if this means that the ideas and notions that are comfortable or dear to him may be overturned.”

David Bohm

However, if the pain and confusion is overcomed, and new, and more general order is found, the reward may overshadow the preceding distress. Apparently, some highly creative people, like Picasso, seem to handle this better than others and may even be curiously attracted to such a chaotic state. Also in scientific research it seems like some people can endure and perhaps be more attracted to the unresolved mysteries than others. Dörfler et al (2018) describes a state called negative capability that scientists need in order to cope in times of transforming theories and changes of paradigms: 

Beyond the engagement with reality (and thus data), the negative capability is also important for an achievement of comprehension when we accept that the reality does not play by the management textbooks, and that researchers inevitably have to face a lack of internal consistency in their emerging understanding. Sometimes inconsistencies will disappear during the research project, but often they can persist for years. Thus, researchers need to develop an ability to cope with such a situation – and they need a framework in which a less than complete internal consistency can be accepted.” 

For this type of creativity, requiring breaking of old reference frames, one may wonder how subjective usefulness is judged in the moment of insight in the creator. It is quite apparent that too narrow biases (boxes) of the old structure must be ignored in favor of wider biases or prior distributions of acceptance of candidate ideas, as we would put it in statistical terms. It is likely that highly creative people use high level biases, as the sensations of wholeness, beauty and harmony, as guidance for their openness to new ideas. David Bohm states that highly creative people, be it scientists or artists alike, seek a sense of wholeness, symmetry, harmony or beauty in their work:

«The new order leads eventually to the creation of new structures having the qualities of harmony and totality, and therefore the feeling of beauty».

David Bohm, in «On creativity».


This may also explain why simplicity, beauty, symmetry and totality tend to be more common measures of scientific validity of theories in some areas of mathematics and physics where there is a lack of experimental data for falsification studies, like for instance in cosmology.

Openness to new experience, as is a known trait of more creative personalities, comes with a cost of increased uncertainty about the actual usefulness of the ideas, only revealed through subsequent analysis and testing. Many have admired the ingenuity of Thomas Edison and his inventions, but he was also not afraid to try, and fail, repeatedly! But every now and then his insight was right.

Secondly, if an old, established structure is broken and a new order is suggested, it is very likely that the novel idea is met with scepticism, rejection,  or even ridicule in the community that still lives under the old structure. A scientist suggesting a shift of paradigm, or an artist creating a completely novel way of expression, risks that the difference in structural bias is too large for acceptance of the suggested new ideas in the community. The burden of proof of usefulness of the new idea, increases with the distance from the established biases.


The neurology of insight

Numerous neurological studies have been conducted using brain scans (e.g. fMRI) during creativity tests, and researchers have gained some knowledge as to which parts or networks of the brain that are active during various stages of creativity. Some studies have shown that divergent thinking and creativity is positively correlated with increased neural activity in the so-called default mode network (DMN) in the brain. This network is typically active when we do not attend strongly to the outer world, but instead are focusing on internal goals, memories or planning. It is also shown to be active when we are preoccupied doing cognitively non-demanding tasks with low amounts of sensory input, like routine work, walking, showering or other moments of serendipity. Neuroscientific studies have also shown that other parts of the brain, making up the so-called executive control network (ECN), is more active when we are attending cognitively or emotionally challenging tasks, like problem solving and decision making. In parallel to David Bohm’s view that the creative process is an iterative process switching back and forth between the stages of insight and fancy, a creative person must own enough flexible cognitive control to be able to switch effectively between the DMN and the ECN networks (Zabelina and Robinson, 2010). Recent neuroimaging studies support this, showing that flexible and dynamic interactions between DMN and ECN is key to creativity (Beaty et al. 2018). Apparently, also a third cognitive network, the so-called salience network (SN), is important here in controlling the interplay between DMN and ECN. 

Hence, the quest for finding the connection between creativity and brain activity has lately switched from a point of view of brain regions to considerations of network connectivity and flexibility. In the previous blog post, the stochastics of divergent thinking, we connected such flexible cognitive control to the ability to switch easily between short and long transitions in the random walk of associative thinking, effectively switching between focused and diffuse states of mind. Apparently this is not only a matter of switching step lengths, but also switching between networks.

So the interplay between the three networks, DMN, ECN and SN, seems to correlate with a (semi-)conscious form of the creative process, in line with the rational insight and rational fancy stages of David Bohm. When it comes to imaginative insight, the Eureka moment type of creativity, a fourth brain network, has gained increasing attention in the last couple of decades. This is the so-called cerebro-cerebellar pathways connecting the cerebral cortices with the cerebellum. 

The importance of the cerebellum in fine tuning and optimizing body movements (motor control) has been known for a long time. It is theorized that the cerebellum is creating fluent and advanced motor control by using predictive models (theory of predictive coding) combining automized movements (basic motor constituents) and performing continuous adjustments based on prediction errors. However, the importance of this brain region in mental processes, has a much shorter recognition in science. The role of the cerebellum also in creative processes has in later years been well elaborated and explored by Larry Vandervert who relates the manipulations of this brain region to creativity by blending of thoughts: “In sum, the cerebellum appears to play a predominant role in the refinement and blending of virtually all repeated movements, thoughts, and emotions».

Although the cerebellum contains more than 75% of all neurons in the brain, its cognitive processes are hidden in the unconscious. It is likely that the tremendous unconscious source of creativity discussed in the stochastics of divergent thinking is due to the skillful manipulations in the cerebellum. Vandervert states that cerebellum is unconsciously generalizing thoughts (as well as movements) using so-called inverse dynamic models: “The inverse dynamics model helps explain how generalizations can be formed outside a person’s conscious awareness. This is a major reason that intuition may seem to leap out of ‘‘nowhere.” The imaginative insights of Bohm may thus be the outcome of these cerebellar processes, and a possible explanation, paralleling the conscious and rational insight discussed above, is an interplay where the cerebellum is supporting, and partly replacing, the ECN in the creative interplay with SN and DMN. In this way conscious and serial manipulation of thoughts may hypothetically be replaced by unconscious, parallel manipulations controlled by the cerebellum.  During the flexible switching of the creative process, the ECN feeds the cerebellum with intentions, interests (biases) and problems to be solved. Further, the DMN provides a rich variety of reshuffled thoughts, memories and ideas, which the cerebellum recombines to fit intrinsic goal oriented models. This is occasionally fed back to ECN to create imaginative and conscious insights, the eureka moments. This is somewhat in line with the ideas of Vandervert: “These refinements in skills and thought occur through the cerebellum, because cerebellar internal models unconsciously drive automaticity and error-correction toward optimization in skills and thought, which is then sent to and consciously experienced in the cerebral cortex.” 

Just like for motor skills, like riding a bike or making the perfect golf swing, the cerebellum has automated primarily consciously controlled functions into unconscious routines. A question is how and when the imaginative insights are delivered to the cerebral cortex as conscious experiences of new ideas and orders. Obviously the news-content must be sufficiently important and relevant to a given context and problem to alert the conscious mind. We may imagine that sudden insight occurs when the unconsciousness finds a good posterior fit of (potentially reshuffled) new experiences into bias structures that we find particularly interesting. This may also partly explain why a-ha moments tend to occur during so-called incubation periods of serendipitous activity shortly after focusing hard on a given problem for some time. The focus period may simply increase the probabilistic value of the prior structures we find particularly interesting or promising for a given problem. This comes in addition to the fact that subsequent defocusing itself may help the signal reach the surface of consciousness easier, simply because the general attention level is lowered and competing focus points are few and weak (weak priors).


Invariance and fractals 

We have discussed how creativity can be understood as the discovery of new order or structure by transforming and reshaping biases, typically by bending, blending or breaking the old mental frames. Since the semi-conscious or unconscious processes seem to be such a rich source of creativity, there appears to be favorable conditions for creative processes when the mind is unfocused. We have touched upon several potential factors in this blog series that can partly explain this powerful property of the unconscious, like parallel processing, reshuffling of association chains, increased processing speed, and weakened biases. All these factors may together generate a favorable cognitive state for creativity; a state where the brain can exploit the fractal properties of biases due to invariance. This sounds mystical, but let me explain.

A fractal can be seen as a structure or pattern which repeats itself or is self-similar at different scales. This part of mathematics is perhaps most famous from the Mandelbrot set as exemplified in Figure 2 where we can see swirls repeat at different scales as we dive into the picture. 

Figure 2: The Mandelbrot set with self-similar patterns repeating itself at different scales.

Several researchers have discussed fractal properties also in the human brain, for instance, in the way that the branching of the neural networks repeats at different scales. However, also in its functioning the brain seems to be fractal, and this may explain how insight occurs, both consciously and unconsciously. The human brain is very good at finding similarities and familiar patterns everywhere. For instance, when we look up at the sky we may suddenly imagine the shape of a rabbit in a big cloud. Perhaps we even have to imagine the rabbit up-side down or with abnormally large ears or legs, but still we see it. The human brain is an extremely effective pattern recognition machine, and it can easily bend, blend or “break-and-rebuild” structures by relocating, rescaling and/or rotating old, familiar patterns. Hence these patterns may be regarded as fractals which can be applied at different scales and in different locations and rotations. During this imaginative process scales seem to be non-important. In statistical terms we may use the term invariance to describe such a condition where location, scales or rotations don’t matter. It may be hypothesized that when we are in a semi-conscious or unconscious state of mind, the brain enters an invariant and fractal mode where new order is more easily generated through bending, blending or breaking. Even time may become invariant in the realm of the unconscious mind, just remember how the speed of association processes are increased dramatically (shrinking time) and elements of thought chains are reshuffled (breaking chronology). 

Liu et al,,2019, who found that the brain appears to be unconsciously reshuffling order of sequences in an attempt to fit new experiences into existing orders and structures, state that this “Generalization of learned structures to new experiences may be facilitated by representing structural information in a format that is independent from its sensory consequences,…” Furthemore, they write that “Keeping structural knowledge independent of particular sensory objects is a form of factorization. Factorization (also called ‘‘disentangling’’; Bengio et al., 2013; Higgins et al., 2017a) means that different coding units (e.g., neurons) represent different factors of variation in the world». Factorization, disentangling and invariance are here all terms describing an objective and somewhat unstructured state that may be envisioned in the unconscious mind, wherein the cerebellum is free to make goal-directed fractal compositions. 

This state of mind where order and structures are broken and transformed, resembles the phase transitions of matter in physics. For instance, when ice melts and forms liquid water, the tight order and structure of ice is broken, and a new structure is formed where water molecules move more freely. Recently a group of mathematicians have come close to prove that so called conformal invariance is a necessary property of phase transitions, the critical state between two phases of matter. Conformal invariance is a more extensive invariance which comprises all the three other invariances mentioned above; location (translational) invariance, scale invariance and rotation invariance. In our context it may be hypothesized that a state of conformal invariance also is a characteristic of the unconscious mind, and that the cognitive flexibility of insight and fancy, as described by David Bohm, can be compared to the phase transitions of matter. The creative process fluctuates between insight and fancy like some physical matter moves in and out of a critical state. From the highly invariant unconscious mind, new structure may crystallize as novel and useful ideas popping into consciousness.

From human creativity I will switch to artificial creativity in the next blog post, and I will return to the notion expressed by McCarthy and colleagues in 1955 about the potential of implementing algorithms that at least can simulate human creativity. The last three posts on the stochastics of human creativity will serve as a reference frame for my discussion on artificial creativity. Stay tuned!

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