What Goes Up Must Come Down


“Why do you think those adverts on TV are repeated so often? “

Many years ago this question was posed in an informal discussion, quite out of any context, by scientist and TV personality Professor Heinz Wolff.  It emerged from an insatiable curiosity about everything that is a hallmark of both the engaged scientist and innovator.  Memories of the day have long faded, except for that question.

Photo by P. G. Champion


The fact that such a mundane question can be posed by so eminent a scientist suggests that the answer might be important.  The same TV advertisements are indeed broadcast repeatedly.  They are expensive and so the benefits of doing so must be appreciable.  We have now reached a point to sketch an outline of what an answer might look like.

Adverts communicate information that enables TV viewers to perceive the value of their associated products or services.  In the vocabulary of this website, the broadcast information creates instances of Consumer Product Interaction with a consequent consumer perception of value.  A viewer may feel a closer association with their sporting hero by wearing the brand he is commissioned to promote.

The raising of value perceptions has been imagined as the elevation of a huge, wobbly marque-like structure referred to as a Value Surface, on which a single point marks an individual’s response at the time of that Consumer Product Interaction.  This value perception may subsequently go up or down depending on whatever information follows.  News of a drug scandal degrades the image of the sportsman and his sponsored products.  The Value Surface in its entirety is forever in an agitated seascape motion that is hopefully nudged upwards by each broadcast advertisement.

One mechanism of action for the advertisements is through the classical conditioning discussed in the previous post.  Just as the dogs of Pavlov could be taught to associate the sound of a bell with the arrival of food, the information and images in the advert may evoke an equivalent response in value perceived for the associated products or services.  Recognition of brand attributes has been associated with conditioned responses by Janiszewski and Warlop (2013) .

The requirement to frequently rebroadcast the same information clearly indicates that the association with value needs continual reinforcement.  This could be necessary to increase the number of recipients or enhance value perceived, that is to increase the overall breadth or height of a Value Surface.  TV advertisements certainly have a huge reach.  It is also possible that residual perceived value following the advertisement broadcast might naturally diminish without the subsequent reinforcement of the message.  One might consider that the advert has a role in propagating ideas as a meme, as discussed in New Economics of Innovation, which is analogous to the viral propagation of genetic information.  At any time there are many other possibly conflicting memes competing for survival in the consciousness of a recipient population.   Advertising agencies and media companies alike have done well out of this silent struggle.

With so much content passing every second through the information environment, markets might well be naturally forgetful.  We will explore this idea in more detail later.  At this point we should note that it is often hard work to raise a Value Surface and then to keep it aloft.  This effort appears in the investments and endeavours made by an enterprise and entrepreneur in making their information valuable.  Next we will transform the Value Surface into a single point that represents perceived value for a whole population of consumers.


The Neural Roots of an Economic Trajectory

The Value Surface concept discussed above and elsewhere is essentially a micro-analysis of the behaviour of a population of consumers[1].  This is needed to construct and interpret the viscoelastic-derived model that has been used to simulate the commercial operations of an enterprise.  To provide a more macroscopic view of that enterprise, we can collapse the three dimensions of the Value Surface into a single point that is representative of the entire value-creating innovative activities at a particular moment in time.

Taking the average across the multiple perceptions of value for a consumer population gives a single measure of height to which a product can be elevated by the endeavours of an enterprise[2].  Clearly some products will be more difficult to raise than others. The resistance to this elevation will be different for different products, and will inversely represent how attractive they are to their consumers. We can then follow this point of average perceived value with time to draw a trajectory of a product through an economic space.  The role of the enterprise is to “fly” the product through this space, as described in the companion Foreground papers: An Economic Trajectory  and Flightpaths and Forgetful Markets.

Here, with more freedom to speculate, we will consider the neural origins of a potential field through which an economic entity might fly.

In Valoris Cognita Barcelona we have considered how a person’s brain may interpret information received through the senses to build and adapt a continuously changing model of reality.  Consciousness may be considered to arise from an elimination of the errors that separate neural cognition from external reality.  It is a descent down an “error surface” to a point that is satisfactory for survival, but which inevitably leaves some unimportant residual error with an associated subjective perception.

Whilst the electrical impulses and neuro-chemical transmission of information that arise in neural cells and synaptic connections is clearly powered by the host individual, a neural model of reality may be changed by this information flow to become less transient and more ordered to some degree by the memories it engenders.  This explanation needs help from an analogy with another energy dissipative system.

In Writing the Information we considered various systems through which energy flows and thereby transforms the system that is its conduit.  One such example was the flow of water down a mountainous terrain.  The water flow itself was driven by its inherent potential energy acquired due to its height.  The direction of flow is not random but clearly follows a path to descend to the lowest point as fast as possible, and in doing so it sculpts distinctive river valleys into the terrain that serve to further accumulate and direct the water flow and erosion.  In summary, whilst the flow originates from the potential energy of the water and is transient, semi-permanent features are created and remain long after their creation.  In these features are written the full history of previous torrents through the energy dissipative erosive events they have engendered.

Could the energy flows through neural circuity have left similar features that we call memories through associated energy dissipative events?

Water Erosion Pattern

Could the information content that is etched into a brain and into individual neural models of reality be the source of potential energy fields we have hypothesised as resisting the elevation of a Value Surface and its associated Economic Trajectory?

Could a continuous neural remodelling response to new information together with the competition for vital attention explain why signals that are not reinforced dissipate leading to a natural forgetfulness of markets?

Can innovation that is making information valuable actually be a physical phenomenon or should we be content to have a suitable physical analogue of this fundamentally social process?

The latter question may not be as outrageous as it may first seem.  We have discussed in Semantics of Information that deletion of information has thermodynamic consequences.  There are similar issues in other domains for which information may have a physical manifestation.


Applying  Landauer’s principle to the information content of the universe  M. Paul Gough (2008) calculates that an information energy makes a significant contribution to the dark energy that is hypothesised to have determined the dynamics of the expanding universe throughout its entire history.


NASA and the European Space Agency.
Hubble_ultra_deep_field_largeNASA’s Hubble telescope reveals around 10,000 galaxies with the deepest view into the history of the Universe.

So why are adverts on TV repeated so often?

Imagine a world without the repeated marketing needed to encourage product purchase.  The dynamics of an economic trajectory indicate that goods may not simply remain frozen in space.  The potential retained within the Value Surface has already been diminished by previous Sale Events.  Now, the inevitably dynamics of descent will be brought into play and there will begin an increasing rate of loss of information in a reversal of the previous ascent phase of the trajectory.  Investment and prices will fall as companies seek to convert the residual potential in the collapsing Value Surface into income and consumers will forget how they once valued the goods.

This dynamic mechanical analogy provides an explanation for why commercial television repeats and repeats again advertisers’ content.  It provides an explanation of why salespersons continually need to repeat and reinforce the value proposition of their products.  So finally we can propose a derivative of the Labour Theory of Value Creation where labour is also working to prevent the depreciation of that value due to a natural forgetfulness of dynamic markets.  Innovation has a role therefore, not only in making information valuable in the first instance, but also in retaining the value of the information and opposing a tendency for that value to decline with time as a product matures.

As it is with commodities and technologies, so it is with whole companies that integrate the value of their various commercial activities.  The value of the company as it appears in its stock market valuation depends ultimately on the effective deployment of capital to propel the company on its own economic journey.  The forgetfulness of the market appears in the fluctuating patterns of valuation of public quoted stock.  Memories are short and a regular injection of good news is needed to counter a fall in value.  Volumes of press releases evidence this common practice. The similarity of the qualitative nature of the economic trajectories of commodities, technologies and companies, whilst these may differ substantially in time and duration, together with the voraciousness of consumers to absorb this “vital” information, point to a similar cause and effect arising from the action of an economic potential field.


Multiple images of beautiful independence might well convince a receptive individual of the transcendental properties of a particular perfume.

In doing so, their need to be repeated on multiple occasions may be essential to overcome a natural forgetfulness of the fragrance market.


 Dior j'adore sm


[1] It may be considered equivalent to the statistical mechanics description of the thermodynamics of a liquid or a gas, which is at the origin or models of economics developed by Paul Samuelson et al.

[2] Some consequences of taking an average measure of value perception are considered in A Labour Theory of Value Creation.

Of Dogs, Men and Crows

About one year ago we set out with a definition of innovation that is making information valuable and with an aim to explore innovation using the physical and biological sciences to add to the understanding of innovation as a social and economic activity.

In the previous posting Valoris Cognita Barcelona this journey led to sketching out of some principles whereby the information content of an innovation might manifest itself in the neural circuitry of the brains of consumers, who might then perceive an associated value.

Unfortunately, consumer brains like all models produce approximations of the real world. There can be no absolute reality in this subjective world, just opinions held to varying degrees of conviction depending on how sensory information fits to the cerebral model an individual consumer uses to understand the world in which he lives.  Furthermore, this cerebral modelling is not a uniquely human capability but is shared with other organisms.

Here we will start a catalogue of examples of other species for which information may be considered valuable.

The classical example of the perception of value associated with information is in the classical conditioning of animal behaviour discovered by Ivan Pavlov in the early years of the 20th century.  Famously, saliva secretion in dogs which normally occurs when they find food can be generated by other stimuli, such as the ringing of a bell, which through repetitive association the dog has learned to indicate the arrival of food.

One might interpret this conditioned response of the dog as valuing the information communicated by the ringing bell as it might value the arrival of the food itself.

Whilst alternative unconditioned responses, that are innate and naturally occurring, appear to be hardwired in deeper and more primitive parts of the brain, learned conditioned responses arise in the cerebral context that is responsible for higher order intelligent behaviour.  The initial neural correlations with the perception of value can thus be identified.


Since the discovery of the physiological basis of classical conditioning there has been widespread application of the concept in marketing and advertising[1].  It is unsurprising to consider that the learned response of Pavlov’s dogs to the various stimuli that provoked their salivation can be associated with the desires of consumers in shopping centres as they encounter the brands that line the shelves therein.  In this case the brand communicates the necessary information for a receptive consumer to perceived value in the associated product.

Wormhole:        Consumer Behaviour: There is a great deal to learn from other fields especially when it comes to consumer motivation and behaviour.


A more recent study of a quite different aspect of animal behaviour, that is to do with the reaction to inequality in the treatment of individuals, also indicates a perception of value in species that enjoy a complex social behaviour.

In 2013, Claudia Wascher and Thomas Bugnyar [2] reported on the behaviour of pairs of crows where one individual is rewarded preferentially in relation to a second.  The birds had learned to associate a token exchange with their reward with food.  The study of Wascher and Bugnyar revealed that the bird’s behaviour depended on the inequality the researchers introduced into the reward system:-

Crow 1

A view from the office window.  Crows and ravens have cognitive abilities similar to primates, especially in their social interactions, in various forms of cooperation and problem solving and with a high selectivity in partner choice and in coalition and alliance formation.

*   If only one bird of a pair was rewarded with food for the same exchange task, this diminished their willingness to participate in the token exchange[3].

*   If one bird received lesser quality food for the same exchange task, this also diminished willingness to participate in the token exchange.

*   A bird receiving lesser quality food for the same exchange task may even choose not to accept their reward, even though they had already paid the cost in the token exchange.

*   If one bird was given food as a gift whilst a second had to “work” for the food through a token exchange, then this also reduced their willingness to participate in the token exchange.

*   Different individuals respond differently to inequity in complex ways, making the above findings apparent in the statistics of the population rather than appearing in the individuals on every occasion.

This response to inequality is interesting in itself as it mirrors human preference for fairness in reward distribution, where even a person receiving a disproportionately higher reward can be dissatisfied by an unequal distribution.  Whilst primates also behave in a similar manner, the inequality response in dogs is determined solely by the presence or absence of the reward and not its quality.  Fish on the other hand appear completely insensitive to inequality.

Crows have a complex social behaviour and accordingly their behavioural response to inequality is highly sensitive.  Furthermore, for this reaction to occur, these birds must show attributes that are particularly relevant to the current discussion on value perception.  This sensitivity to inequality requires the birds to have:-

  • An inherent perception of the relative value of different items upon which their response to inequality is determined.
  • An inherent perception that the cost (in terms of token exchange) needs to be equivalent for the same reward as recognised in the received food.
  • A perception that the value of a reward is inherently related to the work required to acquire it.

So it seems that the Value Surface concept and even a Labour Theory of Value have behavioural roots that may have arisen independently in species of mammals and birds that share complex social interactions within their communities[4].

Smith, Ricardo and Marx could recognise their classical articulation of economic motivation in this fascinating insight into animal behaviour that appears to be associated with the co-operative tendencies of the species concerned.  All three repeatedly emphasised that such economic behaviour emerges through social interaction, and so it seems.  However, it also appears that social relationships can condition the associated neural responses in individuals.

It is therefore significant to note that perceptions of value, whilst they must originate through cognition and brain function, are fundamentally associated with a society and the complex social relationships that exist therein.  There is such a thing as society.  Furthermore, Sale Events are dependent on more than a simple individual comparison of cost and benefit.  Environmental factors within the society play a role, one of which is the fairness and equality that underpin the transactional behaviour.



[1] Limbad, Shaileshkumar J.  “The Application of Classical Conditioning Theory in Advertisements” International Journal of Marketing and Technology3.4 (Apr 2013): 197-207.

[2] Wascher CAF, Bugnyar T (2013)  Behavioral Responses to Inequity in Reward Distribution and Working Effort in Crows and Ravens. PLoS ONE 8(2): e56885. doi:10.1371/journal.pone.0056885

[3] The willingness to participate in the token exchange is referred to as “exchange performance” and is the likelihood a token exchange will occur.  Crows like humans are varied in their responses to stimuli as is recognised in the Value Surface concept.

[4] This explanation seems more plausible than the alternative that these behavioural traits arose when birds and mammals had a common ancestry, that was around 320 million years ago.

Valoris Cognita Barcelona

In memory of Joe Egan, born 25th February 1916

Here we move tentatively into the terra incognito of the physiology of value perception.  Expect amendments to follow.

The previous posting on Ubiquitous Error Elimination leads us to consider that value perceptions gained through the automatic numerical meanderings of a Least Squares Method fitted model may have something in common with value perceived by real consumers of some actual goods.

A point of commonality is to consider one’s brain as a model that delivers consciousness of observed reality.  The observations are sensory inputs that comprise many analog signals, which an internal perception must seek to organise into a cognitive model with a minimum error value.  Although the physiological processes are largely unknown, one might expect some form of neural modelling and fitting to observed reality as part of the emergence of conscious awareness.  If so, then all such model fitting will be subject to the general principles of navigating a complex error surface.[1]

In The Grand Design (Bantam Books, New York, 2010) Stephen Hawking and Leonard Mlodinow set out to address some very big questions employing “model-dependent realism”, which assumes our brains form models of the world based on information received through the senses.  There is no definitive true reality and many such models can co-exist and may be adopted dependent on their usefulness and value.  Such individual perceptions of an external reality are likely to depend on intrinsic assumptions and will probably find acceptable limits of error that are sufficient to ensure survival.  To do more, at least in a primitive society, would be a waste of energy.

If one could link the concept of a potential field that we have hypothesised as acting to constrain the creation of value in the raising of a Value Surface, to an error surface associated with cognition and perception, then this could indicate some physiological foundations for the earlier hypothesising.  Some physiological potential must be driving a descent down an individual’s cognitive error surface to achieve a reliable perception of reality.  Otherwise one’s consciousness would have no physical cost and Maxwell’s Demon might happily defy the 2nd law of thermodynamics.  Information that confers survival, in a primitive society, and perhaps quality of life in a modern society, must be classified as more valuable, indicating a higher use-value to external objects or a greater exchange value, than a random replication of useless information.  Hence information can be made valuable through the very processes of biological perception.

This sketching out of an association between the physics of value perception and the biological origins of consciousness is entirely speculative.  A deeper analysis of this association must await another day.  However, the general concept of an intrinsic neural model that is fitted to observed reality does lead to some interesting observations.

This concept explains individual differences of opinion that are reflected in an oscillating Value Surface.  Individual perceptions of the real world clearly differ.  The start points to fit a neural model to these perceptions certainly should differ.  Different acceptable local minima on the error surface may provide different individuals with a different interpretation of the same reality.  Human beings probably do not process sensory data exactly in the same way and clearly can reach different conclusions when given similar scenarios to manage.  If people behaved as automaton robots, then each commodity Value Surface would be a rigid plane of equal valuation.

Yet people’s opinions and beliefs are extremely stable for such a dynamic fitting of internal model with external reality.  Such stability could arise if the start of every new minima search begins at the most recent minima for a comparable reality, perhaps retrieved from memory.  In this case only the change from the previous reality needs to be reconstructed in the modified internal model, which then provides the next start point in a continual modification of an internal neural model to reflect changing perceptions of a real world.

Barcelona Seafront

Whilst cogitating on this very subject of the fundamental origins of the conscious mind, the author was sitting on a bench on Barcelona waterfront.  A very brief interruption was made by a smart thirty-something year old who mixed languages rapidly in an urgent attempt to communicate.  Within ten seconds the chap had disappeared along with a bag containing everything that was valuable, snatched by a second person during the distraction.  Passport, wallet, travel tickets, laptop, money all had disappeared.  Yet in disbelief I imagined I could see my familiar grey stolen rucksack where it should have been, on the bench beside me, for a good few seconds before grim reality fully allowed itself to be recognised.  Reality had changed too quickly and it seemed the refitting of my internal model was taking long enough to notice the processing delay.  Later on at the UK Passport Office, I was informed that Barcelona is the bag-snatch capital of Europe and had I known this, the adjustment to the new reality might have been smoother.  Or maybe I would have protected my belongings with more conscious deliberation.

Several years on, the memory of that minor Barcelona trauma is fresh and easy to recall.

As considered in “Writing the Information”, can such vivid memories be the river valleys etched into the error surface of my consciousness by the cascading experience of these earlier events?  This is a subjective and even metaphysical suggestion, but such a cognitive system should certainly be an attribute in favour of survival and as such could be a selected epigenetic trait.  Important information would be considered valuable by its hosts.  I will be more careful of my luggage on any future visit to Barcelona[2].

Whatever are the mental mechanism and however current controversies on the nature of the mind and consciousness play out in the future, the subject is central to understanding innovation.  Not only are the intellectual processes that act on information at the very origins of innovation, but the subjective appreciation of value by the consumer, whatever the product of the imagination, can be traced back to its source in the obscure processing of the human brain and its constituent 100 billion information processing neuron cells.


Back in Barcelona in 1887 Santiago Ramón y Cajal started to work with a new Golgi staining method that used a silver preparation which, for the first time, enabled neurons to be clearly visible through a microscope.  It was the start of the modern discipline of neuroscience.  Ramón y Cajal used the Golgi method to produce many graphical illustrations of complex neuronal shapes.  On observing these cellular structures exemplified below, it is difficult not to see similarities to the dendritic patterns considered in “Writing the Information”, and to infer that the associated metaphor might extend into this neuroscience domain.  That is, the tree-like neuronal patterns once again infer, albeit circumstantially, that an energy transmission function is at the heart of these microscopic constituent cellular elements of the brain and central nervous system.

Santiago Ramón y Cajal shared a Nobel Prize with Camillo Golgi recognising their work on the structure of the nervous system which today forms a “Neuron Doctrine” that is a basis of the current understanding of the anatomy and physiology of the central nervous system.


Purkinje Neuron

Drawing of Purkinje neuron by Santiago Ramón y Cajal, 1899;
Instituto Santiago Ramón y Cajal, Madrid, Spain.
Acknowledgement to Wikipedia: http://en.wikipedia.org/wiki/File:PurkinjeCell.jpg

The dendritic structure of neuron anatomy and physiology enables the cellular behaviour to be mapped onto the generic “Green Box of Innovation” template introduced earlier.  In this case, an electrical signal flows from the multiply connected and complex dendritic structures, through to a central cell nucleus and a single axon strand of connected cells that can reach across millimetres, to stretch out to a branched terminal region, there to connect to dendrites from neighbouring neurons.  The axon-dendrite connection is known as a synapse in which a communicated signal is transferred by chemical means.  Here the information transfer through the synapse requires a transformation of electrical to chemical energy in neurotransmitters and then back to electrical energy as the neurotransmitter binds to synaptic cell receptors to begin the transmission through the next dendritic link of a connected neuron.


Neuronal Green Box


A synaptic link connecting neurons can either excite or inhibit the transmission of an electrical signal, known as an action potential in connected dendrite links. Perhaps 10,000 such dendrite signals converge on a cell nucleus to give rise to a single event which occurs at the axon hillock, the point where the filamentous axon connects with the cell nucleus.  This integration of the many dendrite signals that need to cross an energy threshold to determine whether that neuron will fire a single electrical pulse through its axon to communicate with its cellular neighbours is a main physiological function of the brain and other parts of the central nervous system.  These pulses may last for only a millisecond and each neuron may contribute to the information flow up to 100 times per second.  Clearly there is much information flowing through the average brain.


We have described an energy transfer process that needs to reach a critical threshold before a neuron will fire and propagate its signal.  Billions of such signals must converge to create a perception of value at a Consumer Product Interaction that is a precursor of a Sale Event.  Again this is an integration of received information into an “all-or-nothing” decision to purchase.  Though differing in terms of scale similarities appear in the energy flows of the action potentials of neural circuitry and those operating on consumer preferences  in the shopping centre.

There are Artificial Intelligence (AI) models that attempt to replicate on a very small scale the manner the brain naturally might function.  Neural networks, an example of which is shown in the figure below, are brain-like numerical models of layers of connected neurons whose connection properties provide a generic set of parameters that can be specified to characterise the behaviour of the system.  These connection parameter values can be estimated by using a Least Square Method, navigating to the lowest point on an error surface between a simulated behaviour and a known “training set” of real output values.  Once the ideal simulation with the smallest error has been found, then the associated neural network parameter values should faithfully reproduce the real world, so long as this is retained within the limited confines defined and exemplified by the training set.

Neural Network

A typical neural network connecting four input neurons to two output neurons
through a single intermediate layer of 6 intermediate neurons.

AI neural networks can be useful as they continuously learn from new data just as humans might.  The predictions they can make can be informative as are human intuitive predictions.  They are also susceptible to weaknesses of ambiguity in human understanding.  There may be many local minima on the error surface to trap the descending Least Squares Method.[3]  Also, like the brain, a neural network model is adaptable to fit with the many diverse challenges an organism might face, but this means the solution is an arbitrary fit to observable data.  There is nothing intrinsic in the model that represents the world that is being simulated, nor are there any overt assumptions that can intelligently be applied to simplify this real world.

In the real brain of the analyst, the real multi-billion neural network can be applied to explore the world using models with some conceptual simplification.  Effectively this is positioning the human processing power at the front end of the entire modelling process.

This is the origin of An Innovative Enterprise Simulation that uses the Method of Least Squares to provide a vision that would otherwise be unavailable to the unassisted human senses.

It is a model to explore the process of innovation itself.



[1] An error surface emerging from the fit of neural systems to physiological signals will certainly comprise a huge number of dimensions.

[2] The points here are discussed in considerable detail in The Believing Brain by Michael Shermer (Constable and Robinson Ltd, London, 2012) who considers that many beliefs are hard-wired into our brains and then consciously rationalised often through the selective use of information and associated mechanisms of bias.

[3] Actually neural network algorithms can apply such mechanical concepts as momentum whereby the speedy descending searching for a minima can overrun the lowest local point and though it might then need to retrace its search, this can avoid getting stuck in a local crevice on the error surface.

Ubiquitous Error Elimination

Evolution by Error Elimination:  There is one feature on the landscape of innovation that has already been recognised and which will arise again in the future, time and time again.  It appears in all innovation management and evolutionary systems.  It is essential for the creation of new knowledge and in the perception of its value.  It is a fundamental process in the building of models and the fitting of these models to the real world.  These are some the guises of the ubiquitous Error Elimination.

In its most fundamental form Error Elimination appears in the epistemology of the philosopher of science Sir Karl Popper.  In The Logic of Scientific Discovery (1934), Popper recognised an asymmetry in the nature of knowledge that whilst no amount of empirical evidence can prove an assertion to be true, a single case alone may prove it to be false.  It follows that no theory can definitively be proven to be true.

In later work Popper went onto explore how scientific knowledge, which originates in the subjective mind of the scientist, goes onto become an “objective” feature of the world.  In Objective Knowledge: An Evolutionary Approach (1972) Popper develops a “three-worlds” view in which all physical artefacts are “World 1” objects and subjective thoughts and ideas belong to “World 2”.  Popper’s “World 3” is populated by things originating through the human mind but which have gone on to have an existence beyond the confines of that mind.  These include abstract concepts, the content of all books, designs, theories, etc.

Popper’s Three WorldsPopper’s Three-Worlds Relationship

Combining the approach to challenge the validity of existing theories with empirical tests designed specifically to bring about their failure, together with the creation of objective scientific knowledge for those theories that survive this ordeal of falsification, led Popper to conclude that scientific knowledge creation proceeds through an evolutionary sequence:-

Problem 1 >> Tentative Solution >> Error Elimination >> Problem 2


Here, the tentative solution to the initiating problem is continually refined in the light of new empirical evidence, until the new data fundamentally conflicts with existing knowledge, which gives rise to a new problem for the cycle to repeat.


Error Elimination Creates Value by Risk Reduction:  In earlier work we have extended the evolutionary epistemology of Karl Popper to reach technology innovations that might emerge from the scientific research upon which the original work of Popper is based (Egan et al., 2013, Williams et al., 2013).   This involves an explicit recognition of a subjective Value Appreciation stage which forms the link between subjective World 2 and objective World 3 in Popper’s evolutionary knowledge theory.

Indeed, for scientific knowledge, Popper describes such a value appreciation that is achieved through inter-subjective testing, expert peer review and publication and through which the knowledge becomes objective.

4-Point Innovation Cycle

Popper’s evolutionary epistemology cycle, including an explicit identification of Value Appreciation

Initially, there is often a high risk that a Tentative Solution will not consistently resolve its initiating problem in practice and proof of concept projects are required to understand and manage this risk.  This conforms to Popper’s Error Elimination stage the output of which may comprise accumulated information on designs, and the technical and commercial evaluations from which to conclude the potential benefits and residual risks of an innovation.  In fact, the reduction in risk though Error Elimination can be interpreted as a creation of value through innovation, as it is the value that is perceived by the consumer of this information.

In terms of the previous “Green Box of Innovation” that provides a generalisation of an innovation process based upon enhancing the value of information, it is the parameters of the “box” that determine the operational form through which input information is transformed into outputs that have utility and value.   Maximising the value of the outputs is once again an application of Error Elimination to discover the parameters that provide the best operational form for the Tentative Solution to resolve the real world problem it is tentatively designed to address.

In a direct analogy with the growth of scientific knowledge, the existing Tentative Solution should be repeatedly challenged.  The empirical information will continue to provide evidence of utility and thereby continually adjust perceptions of value.  Hence, feedback loops operate through which the value of the Tentative Solution can be enhanced through the Error Elimination process.


Error Elimination by Least Squares:   An innovator may deploy a powerful cocktail of creativity, intuition and experience to make a Tentative Solution relevant and valuable by Error Elimination.  Computers are not gifted with such human capabilities, but on the other hand they excel in their relentless ability the crunch numbers.

The Least Squares method is one of a number of numerical optimisation techniques whereby outputs of a computer simulation can be ‘fitted’ to real-world data.  To do this, some starting values of the model parameters are selected, without knowledge, and a simulated behaviour is derived.  The simulated outputs are compared with real-life and the difference is a measure of the error of that simulation.  This initial error can indicate how to adjust the model parameters to achieve a better fit to the empirical data.  The Least Squares approach enables a further better guess at the model parameters and onward thus rolls an iterative process of Error Elimination to continually improve upon the match between the simulated and the real, to minimize the error and hone in upon parameter values that may provide a new insight into the real world through the window of a best-fit model and its parameters that now describe real behaviour.

Error Elimination we have seen to be part of the process of innovation.  With the Least Squares method it becomes an algorithmic procedure to navigate an error surface.  It works as follows.

It is as though a blind wanderer is placed into a mountainous terrain (for a two parameter model, where the error is a vertical third dimension) with the task of finding the point of lowest altitude, for at this point of minimum error there can be found some useful insight.  Her tool is a stick of enormously variable length through which she can perceive the elevation of the surrounding landscape.  Down steeply sloping hillsides her stick will extend to accelerate descent and avoid the confusion of small rocky undulations.  Into the valley her guide is shortened to follow a meandering contour, always descending towards her goal.  When the topography becomes tortuous, progress is restricted to very small steps, frustrating advancement as the blind wanderer must squeeze through each crevice eventually perhaps to expose wider valleys.  Finally, when all around is higher from the shortest to the longest reach, the wanderer may wonder if she is at the unique point of minimum error.  The wanderer may mark that spot and start again and then again from distant and disparate origins to confirm uniqueness[1], although this might not be necessary.  She may have acquired a valuable insight.

Watching the Least Squares algorithm operate in the virtual world of a computer, it is easy to imagine the numerical model as a blind wanderer seeking the best fit to measurements of reality.  The patterns of descent show a striking resemblance to those previously described in “Writing the Information”, although the topography of an error surface runs through n+1 dimensions, where n is the number of model parameters.   However, this complexity is not relevant for the Least Squares algorithm as Error Elimination proceeds just as it would in our familiar three dimensions.

In an ideal world the final error could be completely eliminated.  It would be an unmistakeable match of a perfect model with perfect data.  Yet all measurements contain their own errors (noise) and in the output of all worldly processes the primary signal is polluted by artefacts which confound perfection with ambiguity.  Also, all models must necessarily be simplifications of the real world, with a judicious ignorance of secondary and tertiary influences.  A perfect model of the real world requires the real world to be the model. For the innovator, it is sufficient to be close enough for practical purposes.

So the innovator must still contribute an essential human element, to innovate upon the structure of the model to better conform to real world observations.  The investigator thus enters into a liaison with the computer to become an n+2 dimension of a hybrid man-machine error surface, which must be navigated to make the model converge towards reality.  Here the inventor is the creative agent giving the model its operational form and the innovator contributes by forging the relationship of the model with reality.  And there may be as many models as pictures hung in a gallery, for value is not in the picture itself but in the understanding gained of its subject.

It is perhaps surprising or even problematic that an automatic computer routine such as Least Squares may be suggested as a means or even a metaphor for innovation.  However, it is not a paradox if the algorithm works on new inputs, so that the path taken to descend the error surface is new and may lead to new and potentially valuable insights.  Of course if this is repeated using the same inputs it would be repetitious and nothing of value could emerge.  Nor is there any accumulation of value as the original path descends to the point of minimum error, as it is only when this point is reached that any value is realised in the insight provided by the “best-fit” model parameters and outputs.

In all the above cases innovation is making information valuable through a process of Error Elimination.  That analogous mechanisms appear in both human and machine applications suggests that the process of innovation itself may not be an entirely social phenomenon.



[1] This may be considered to be a rather trivial instance of Popper’s challenge of falsification.

Writing the Information

For decades school classrooms have echoed with a chorus describing the water cycle: “evaporation, transpiration, condensation, precipitation, run-off”.  The sun heats the waters of the ocean.  Thermal energy beamed down onto the ocean surface agitates water molecules to an extent that some are able to cross the energy barrier at the ocean surface to begin an airborne journey.  Thermal effects cause the moist air to rise as the potential energy of the heavier, colder air displaces the warm vapours to higher altitudes, until they reach an equilibrium height in the gentle folds of clouds.  Prevailing winds blow the clouds towards land, to rise further into foothills overhung by a slate grey cloudscape in which the moisture condenses into drops of relentless drizzle.

As this rain falls the potential energy gained when the sun earlier had heated the ocean surface is transformed into a kinetic energy in the falling droplets.  In isolation this energy is miniscule.  The smallest drops coalesce into bigger ones that can then collect in tiny trickles that run for seconds down a window that faces into the rain.  These patterns are not random but are choreographed by the Principle of Least Action.

The window glass appears unaffected by the downpour, yet it too is behaving like a liquid that is flowing over centuries rather than seconds!

As the raindrops collect together to form rivulets and streams, they combine their energies to become an erosive torrent.  Rain engorged streams cascade down mountainous slopes.  Some potential energy in the water is diverted into creating the micro-fractures of erosion, through which steep river valleys will eventually be sculpted.  These sharp ravines may be assumed to be a natural consequence of energy flow by a carrier material, which in this case is water.

Water Erosion Pattern

The direction taken by streams, as well as the patterns of erosion of canyons and valleys, are clearly not random but again co-ordinated and optimised by the Principle of Least Action.  Macroscopically the descending water converts its potential energy into kinetic energy as rapidly as possible.  Microscopically the energy transferred and dissipated through the erosion shown above can be considered analogous to the accumulated effect of micro-fracture events in a viscoelastic material.

This accumulation of microscopic erosion events is the information content that describes the creation of the river valley over time.  That is, in an ideal sense, the energy passing through the water cycle forms the conduit through which the water flows and optimises its design to comply with the Principle of Least Action.  The associated information content is written by this process.  It is a feature of the environment and is unrelated to any living agent.  The information that is written by the water cycle has a syntax and meaning in the accumulation of the erosive events with time, but has no associated value.  Simply the energy and information content are linked by the physics of the system.

And so it was for millennia that rivers became terrestrial conduits for energy flow.  Then a new form of conduit emerged to process more of the vast energy resource that showered down upon the early Earth.  About four billion years ago biology was born.  Soon thereafter solar energy began to be captured by the photosynthetic activity of Stromatolites, beginning the sequence through which this energy eventually would pass through the bioenergetic transformations of the food chain.  Energy is passed from vegetable to animal, from prey to predator, assuming the predator is able to catch its prey.  The energy is passed from a fallen leaf into the soil, into bacteria and on into further tributaries of the food chain.  The energy each biological organism receives enables it to sustain itself to the search for more food and to reproduce.

A tree is one such organism deserving attention as a biological equivalent of the river valley.  Trees have common features but as individuals no two are alike due to the information written into their physical structure.  To receive solar energy a tree must extend up towards the forest canopy and position the photosynthetic chemical factories in its leaves to be aligned to the sunlight.  Unfortunately, the descending sunlight may become blocked by many obstacles, notably by its own boughs or those of adjacent trees.  Growth is therefore a sequence of reactions to seek the essential sunlight.  Hence the contortion of an arboreal structure and the shedding of the deadwood that fails in its quest to reach the sunlight.

Tree Pattern

As is the case of the river valley, the realignment of the growing tree may be considered as events analogous to micro-fracture events in the physical domains.  This accumulated sequence of events then provides the information that describes the tree through its life; information also has a syntax and meaning.  One might speculate that this information has value, at least for the individual tree as it determines its survival.

Do we underestimate the power of plants and trees?   bbc.com, 20th Nov 2015

As energy captured by photosynthesis in plants cascades down the food chain, it supports the development of other organisms.  Through this throughput of energy there is information content in those same living organisms, just as in the tree, which supports their survival.  For an intelligent agent this is the information that enables their participation in an economic society both as producer and consumer.  The throughput of energy over time creates the information that is the intelligence of the agent.  Furthermore, deployment of this same energy of the intelligent agent in labour creates or replicates the information in the product or service of that labour and thereby creates value from their economic activity.

Let us return to the earlier mountainous cascade, where now an intelligent agent is able to develop another system through which energy is able to flow.  The potential energy and kinetic energy of the torrents that race down the steep hillsides can be harvested and deployed elsewhere.

A Highland Electricity Company elects to obstruct a particularly fast-flowing river with a hydroelectric dam and directs the water flow through its turbines.  A reservoir of water with an enormous potential energy builds up behind the dam, but this energy is insufficient to breach the mechanical strength of the obstacle – fortunately the dam holds firm.  The energy that once propelled the water through turbulent streams is now controlled and set for harvesting.  As water pours through turbine channels, the blades are rotated and the water leaves slightly subdued, stripped of a portion of its kinetic energy.  Generators have converted some of this passing energy into an electric potential.

As the river’s remaining energy takes the water to the sea, the electrical energy now flows through a different channel, a national grid of high-tension cables to power a society.  The intelligent agent has thus developed a further energy conduit that is also filled with energy obtained from the combustion of fossil fuels.   That energy also came from the sun and fell onto primordial forests in an earlier epoch from which the chemical energy of the oil and gas and coal has now found freedom to flow again through the electrical conduits.

 Foundry As electricity is consumed the electrical energy is again transformed, in some cases to produce heat and melt metallic ingots of a foundry and cast these into the shapes of a preformed item of economic production.  In this foundry, materials, manpower and machines combine their energies in manufacturing operations.  The effect is to enhance the information content of the fabricated goods.  In this case the information has a syntax and meaning that can be interpreted by consumers in a perception of the value of the goods.

Each value adding step can be interpreted as the movement of the fabricated goods through an economic potential field.  A further utilisation of terrestrial energy resources propels these manufactured commodities to a higher economic potential.  Millions of individual blips on the Value Surface of the goods are thus created to record their elevated value.

A road network is no less a conduit for energy flow than a river valley or a tree.  Human beings as producers depart on the minor tributaries and pour down major transport links to deliver their labour.  Manufactured goods are loaded onto juggernauts, ships and through huge container ports to carry them onward through supply chains.  Through the motorways, main roads and side roads of an economy the goods are carried to the shelves of the retail outlets to be made available to a geographically distributed consumer population.   Human beings as consumers enter the same transport networks to find the goods and services that they need.   The information content can be drawn into maps and GPS devices.

Elsewhere we have considered as equivalent the information communicated by the distribution of some fabricated goods and the information communicated through media channels that advertise those same goods.  Precisely the same equivalence may formed between the transport networks  and telecommunications networks that communicate information generated by intelligent agents and which enable those agents to integrate their activity in an economic society.  The society thus brings together all the energy contributions of its component parts.  At this high level the associated information content includes the rules and regulations that enable the society to function, as well as the information that is shared between the component parts.

Whereas water is the carrier of energy in the river and has created the information content of the valley, and the passage of energy through the food chain has fashioned the design of trees and other organisms that make up this chain, the energy in the materials, manpower and machines are also the source of the information content of the fabricated goods and services.  Likewise, the energy that drives an economy is the source of the information content of its transportation and telecommunications infrastructures and the governance of the society itself.  Roads, railways, relays and regulations that are disused will eventually meet the same fate as the dried river bed or the deadwood of the tree.

We have described specific examples of a generic process where the passage of energy through a system causes the system to change, and discrete events record that change in the information content of the system.  A system’s information content can therefore be considered to be a legacy of this energy throughput:-

System Carrier Energy Information Content
River Water Potential, Kinetic Erosion of the river valley
Tree Carbohydrates, ATP, etc. Chemical Physical structure of the tree
Food Chain Primitive Organisms and Species Chemical, Kinetic Behaviour to survive and reproduce
Intelligent Agent Food, Fossil Fuels, Human*, etc. Chemical, Kinetic, Electrical (neural) Production and consumption
Commercial Organisation Human*, Machines and Materials Chemical, Electrical Potential# Product or Service
Power Generation Water, Fossil Fuels, Wind, Nuclear Electrical Electricity distribution network
Transportation and Telecommunication Fossil Fuels,

Human*, Machines.

Chemical, Electrical,

Kinetic, Potential#

Transport and telecoms networks
Society Human* Potential# Governance, Legal, Press, Operational Routines

* Human beings as innovator, producer and consumer of goods and services and a carrier of the chemical energy obtained through the food chain.  # Potential energy based on the assumption of an economic potential field

In the diagram below the connected conduits from the table above enable the energy throughput through which the information content of the system  (blue boxes) is written.  In yellow are sources of energy which enter the system from external sources and storage.

Energy Conduits


One final thought:  In the effort to understand this article you will have consumed energy from the food chain.  A third of this energy passes through your brain and hopefully this will have etched a memory of your cogitations into the information content of the neural circuits that form the blue box that is your brain!  It will be the information that enables you to perceive the value of the contents of this page.


The Value of Information

InnovationMaking Information Valuable.  In the previous posting “On Value, Capital and Energy” we sought to make sense of this short definition of innovation by considering what is meant by “Value”.  For this we needed to go back to the works of the classical economists who concerned themselves very much with this particular subject.  Now we shall do the same for “Information”.

To state that information can be valuable is hardly controversial.  Information can be extremely valuable.  Knowing in advance information that could affect the price of a company’s shares can lead to financial gains.  Insider trading is illegal as it distorts a stock market in which all agents are intended to have equal access to the same valuable information.  High frequency trading can expedite access to this information by milliseconds, a short interval that also can be important.

In On Value, Capital and Energy the creation of value is associated with the bioenergetics of the innovator, and specifically with the treatment of value as a form of potential energy.  To discuss information in the same terms it is necessary to form a similar association between information and energy.

Information is physically encoded in many forms.  Indeed whether it is the storage of information in DNA, in computer memory or in the neural circuits of people, one can assume that information is at least in part formed through the organisation of some physical material.

The organisation of a physical system with higher information content is associated with the system’s energy.  This is most famously demonstrated by Maxwell’s Demon.  In 1867 Scottish physicist James Clerk Maxwell imagined an intelligent being capable of operating a trap-door in a wall inside a closed gas-filled chamber and thereby segregating fast moving “hot” gas molecules from slow “cold” ones where normally these molecules are randomly mixed together.  By making this selection the Demon can produce a machine that does mechanical work (a Szilard Engine) – in doing this the Demon can convert pure heat to mechanical energy.  This is impossible according to the 2nd law of thermodynamics – it suggests perpetual motion is possible and that time can reverse its direction!

Maxwells Demon

Figure 1: Maxwell’s Demon[1]

It appears that to resolve this Maxwell’s Demon paradox, the intelligent Demon must identify each fast moving molecule, operate the trap-door and then forget the information before repeating the cycle (or at least have a finite memory).  It is in the act of deleting information that energy (heat) is released and the entropy of the universe is increased to remain compatible with the laws of thermodynamics.  In a more practical sense, this same concept appears in Landauer’s Principle that has shown that the irreversible deletion of information in a computational operation must be accompanied by a dissipation of energy as heat.  On the other hand, the replication of information does not necessarily require any additional energy input.  Such considerations lead to a physical theory of information[2].

The deletion of information in a dynamic sense is the irreversible flow of information from its physical media of storage.  If such an information outflow ends with the increase of entropy, it is reasonable to posit a hypothesis that information content in a physical system is linked to the system’s energy.

In the biological domain, the commencement of information replication could be considered to coincide with the origins of life.  In this most primitive form, information must have been encoded in chemical sequences on molecular strands such as DNA, which must have had the essential and original property of self-replication, thereby automatically copying information and initiating a mechanism for population growth through replication.  From this simple molecular replication has arisen the development of cellular entities where information content has increased and which is now encoding physical signals that determine the survival of the organism.  Evolution of living systems can be considered as the development of the information content of an organism in response to environmental challenges it faces.  In this case, one might consider evolution through natural selection as a means to increase the “value” of this information.

This association of innovation and evolution is further discussed in New Economics of Innovation.

The information content of living organisms has thus evolved to become a principal determinant of their survival.  Information that confers advantages to an organism to be better adapted to its environment, as might be achieved by a mutation of genetic coding for example, could be construed to have value to the organism and indeed to the species[3].  One genetic sequence is then not the same as another, as the more valuable is associated with superior attributes.  This long process of biological evolution has led to the eventual development of an intelligence extending the concept of value beyond that which favours simple genetic replication and into epigenetic mechanisms by which information allows organisms to be increasingly responsive to their environment.  Information such as an aversion to snakes will aid survival, and this valuable information is shared as a natural reaction by many different biological species.

From this epigenetic well-spring, the value of information can thus be traced as an energetic phenomenon, driven by a growth of the brain and the intelligence that the organ bestows, and which is a consequence of metabolic biological energy transformations.

At some point between the emergence of self-replicating biomolecules and the world as we know it today economic activities became established, in which the notion of value is further enlarged to be related to the production and trade of goods and services.  Here information must be embedded in the traded commodities and transactions are based on an appreciation of value that this information conveys.

In an advanced society, the path has moved away from value as being related directly with survival, to a more extensive set of social objectives that we might list as being the ingredients of daily life.

The bioenergetic transformations converting food to the physical and mental activity of the worker have been described.  The transformation of the raw materials into the finished goods through expenditure of the worker’s energy fundamentally is a process of adding information and through this adding value.  Capital deployed in the production facility serves to improve productivity by enhancing this value creation.

As a component flows down a production line, at each stage with more labour and capital deployed, more value is added as more information content is added into the component.  Finished goods will then be shipped through global distribution channels, with the additional energies of labour and transport combining to further increase the value of the goods as they are brought into proximity with their eventual customer.  At the same time, information about the products is flowing through multiple marketing and advertising channels, with the intention of further enhancing the value of the products in the minds of the consumer.  Either by the information gained by direct contact with the goods or through the surrogate means of advertising, the value of the goods is perceived in the minds of consumers and compared with the price.  If the comparison is favourable the goods can be sold and money should flow in the opposite direction as all intermediaries in the chain of supply are reimbursed.

We have developed a Value Surface representation in which the amalgamated perception of value for a population of consumers of a particular commodity can be linked to the energy involved in the creation and replication of this value.  Now we are able to interpret the height of the Value Surface to be fundamentally related to the product information that is received by the consumer.  Delete this information and the associated energy is lost, according to Laudauer’s Principle.

The role of the innovator and the entrepreneur is to ensure that energy expended on the fabrication of their commodities has created and disseminated information that is perceived to be of sufficient value for the goods to be sold at a price that satisfactorily reimburses the producers.  The innovator’s job is to make the commodities easy to lift in a prevailing economic potential field.  In other words:  Innovation is Making Information Valuable.



[1] Image from: https://commons.wikimedia.org/wiki/File:Maxwell%27s_demon.svg.  Please see terms and conditions for reuse.

[2]   A highly readable insight into theory of information and its thermodynamic background is given by M. B. Plenio and V. Vitelli in The physics of forgetting: Landauer’s erasure principle and information theory. Contemporary Physics, 2001, volume 42, number 1, pages 25- 60

[3] As considered in detail in The Selfish Gene by Richard Dawkins