Lesson 29

The search for illogicality enables an inventive logic!

4.2.2Uncertainty

Everything, I do not know, yet, I am conscious of plenty.

from: Faust, First Part of the Tragedy, Scene 7 by Johann Wolfgang von Goethe 1808 [1]

Polemics are the parents of all things, as Heraclitus has stated. In fact, the Greek word “polemics” in Heraclitus’s fragment B53 comprises dispute, conflict, quarrel, and war. Scientifically, however, conflicts are not a question of warfare but just of disputable reasoning or complementary physical measurements.

The conflict of complementary physical properties was acknowledged in 1927 by Heisenberg as a novel law of nature called “the uncertainty principle”. It states that measurable values have to be always uncertain—at least to the amount of Planck’s constant. Indeed, it can be observed that quantum particles are found outside a physical boundary, when their uncertainty in space or their potential of energy reaches beyond the given limits. This is called “quantum tunneling” because the object drives through the barrier like a tunnel. And this effect can explain the fission of radionuclear atoms and stands therefore as an objectivated truth.

We do not know extensively the efforts of Heisenberg to convince his colleagues about this new comprehension in physics. Yet, certainly, he had to defend it against all odds. In his memorial report he mentioned an exhausting dispute with Bohr in Denmark about an appropriate understanding, today known as the Copenhagen interpretation. Sometimes, a considerable disputability is required in order to make new things happen. Since Osborn’s checklist provides a quantity of questions to start a development, a similar amount of techniques is required to tame down the choice at research.

The art of disputation is named after the related Greek goddess Eris as eristic. This aspect for the management of inventions and innovations is mostly neglected or inherently implemented in the general scientific education by academic debating clubs. However, it is an essential ability for management practice since each manager has to state and to argue an unaccomplished novelty at the very beginning of a project case—otherwise it would not be new. Any idea for a research is initially grounded just on a hopefully reliable and sound argumentation, as long as it is not confirmed by a real and factual execution. Objectively, an idea cannot be justified but by arguments. As already mentioned, research is somewhat suspended on the factual side.

Consequently, an innovation manager has to defend a case reasonably until facts can be furnished. And this unassigned argumentation is also a creative activity to obtain some resilient founding for the research on an utopist hypothesis.

Indeed, in many cases the professional request for suitable arguments turns out to be quite useful, because a deeper understanding and an extended analysis are obtained. This aspect of a dispute is called dialectic, meaning intelligence, and insight—yet, sometimes understood as hairsplitting finickiness or logomachy. If there is a lack of suitable arguments, in awkward cases, dialectics may lead to frustration, missed opportunities and false failures. Hence, it seems appropriate to know some eristic techniques, meaning the justification of any case, although with uncertain truth.

Within the posthumous scripts of Schopenhauer a collection of 38 argumentative tricks was found, in order to argue and hold any proposition. And he described the necessity to resort to tricks in a most comprehensible way:

Eristic is the art of disputing, and of disputing in such a way as to hold one’s own, whether one is in the right or the wrong. A man may be objectively in the right, and nevertheless in the eyes of bystanders, and sometimes in his own, he may come off worst. For example, I may advance a proof of some assertion, and my adversary may refute the proof, and thus appear to have refuted the assertion, for which there may, nevertheless, be other proofs. In this case, of course, my adversary and I change places: He comes off best, although, as a matter of fact, he is in the wrong. [100]

For a practical inspection, training, and application, the 38 tricks can be allocated and structured by nine action fields during a dispute:27

First, there are three tricks to refuse a proposition: An extension of the field of application for the proposition forces the opposing party to be more and more specific, until just insignificant particularities are disputable. A specific assignment or homonymy of the applied wording to another meaning will disperse a proposition. For instance, an attribute like “strong” can be understood by different impressions, like color, force, sound or mood, which can be arbitrarily (mis-)understood. And any generalization of a proposition will become absurd, non-sensed, and refuted sooner or later, for example, an exaggeration about validity, duration, durability, and acceptability.

Second, there are three tricks to prepare an own proposition: Concealment by interspersed undisputable statements, which cannot be refused anymore later on but result in a framework for the final proposition. An irritation by obviously false statements, which later on are sacrificed as concessions but allow to push other statements, especially the important ones. And the hiding of a proposition in a general postulation, which is previously explained by particularities, unsuspicious platitudes or innocent wording but subsequently are generalized, concretized or stated more precisely in a suitable manner.

Third, there are five tricks to embarrass the opposing party about its ignorance: An admission of the statements encourages more and more explanations, which comprise some inconsistencies and suspicious aspects ready for later inquiries. A voluntary misinterpretation causes some imprudent comments, which are easy to refute. A disregard of the argumentation and a conclusion by just following one’s own logic constantly detours the logic of the opponent. A pretention of an admitted decision or just a selected choice of alternatives baffles an argumentation without being precise and committed. And a prematurity in conclusion of results allows the presentation of specific admissions without justification.

Fourth, there are four tricks to screw meanings, propositions, and arguments: A metaphorical diction, which awards the proposition a favorable or unfavorable taste, for example, an inventive ideation or a suicidal ideation. A selection of detrimental alternatives, which causes the opponent to choose the least evil, however, still an advantage for the own proposition. An audacious conclusion proclaiming the proof of one’s own proposition—though defeated—sometimes work. A feint of two or more propositions, which can be proved just for one, yet is extended to both or all of them.

Fifth, there are seven tricks to decompose the credibility of the opponent: A questioning about former positions and opinions or similar topics, which have turned out wrong, makes the opponent incredible, at least for bystanders. A subtle distinction of the opponent’s wording within a particular case study, where the words have another meaning, is apt for lasting disputes without any progress. An interruptive change of the subject allows placing novel meanings, propositions, and arguments, which insinuate at least some doubts, if the opponent needs time to follow. A generalization of arguments prohibits taking exact position and becoming vulnerable, since “in general” everything is somehow true. An implication of additional unproved arguments in the argumentation allows drawing favorable conclusions regardless of counter-propositions, because in the end there is mostly no time to check all correlations. An imitation of an unfair proposition reveals the unfairness without going into the details. And a misinterpretation of an opponent’s argument avoids a detrimental conclusion, but gives the opportunity to speak about creditability, instead.

Sixth, there are four tricks to manipulate the opponent: A seducement to exaggerate the statements by steady objection, causing more and more explanations that turn out unsustainable in the end. A false understanding by syllogism of the opponent’s argumentation, which contradicts a proposition or a general accepted truth, causes embarrassment, although the conclusion was not rightly taken. One or several particulate counterexamples defeat a general proposition, in spite of a proof, whether the counterexample is right, relevant or significant in this generality, but the objection of an objection is always controversial. And a reversal of a conclusion quite often raises an objection, for example, the disbelief due to a lack of facts is reversed by the demand to belief first in order to recognize some facts.

Seventh, there are three tricks to manipulate the dispute: A persistence to misunderstand, ignore or conclude wrong—as already mentioned—causes anger or embarrassment, which can be interpreted, as if the opponent is threatened in fact. A persuasion of the audience by means of feigned expertise forces the opponent to instruct the laymen in order to prevent unjustified agreement—yet a plausible simplicity is accredited with more confidence than a complicated instruction. And a diversion of the attention with regard to further, other or broader topics avoids a direct confrontation and decision, but swivels to endless palaver, until something is decided without agreement due to a lack of time.

Eighth, there a five tricks to leave the dispute: An appeal to an acknowledged authority states a result, for example, by citation, which is hardly confirmable by origin, context, relation or relevance in time—but may be due to another originator, topic, sense or a doubtable source. A denial of comprehensibility causes an impression to the audience that the argumentation is dismissed and gets undecidable, because the speakers are generally accredited with certain authority; and if one denies comprehensibleness, the topic is probably too complicated. An assignment of an argument to a category that has been already rejected makes a vicious circle of argumentation, where nothing comes forward any more. A disclaim of practical relevance of the result seems to settle the case without any necessity of the dispute ever, because facts to prove or refute a proposition are absolutely true—and need no dispute at all. And a certain insistence and inquiry of several statements does not produce new arguments, yet it conveys an impression to bystanders that the opposing party has still some considerations to accomplish.

Finally, and ninth, there are four tricks to finish a dispute: An exposure of the intentions and interests of the opponent insinuates that a contrary result is inacceptable from the outset—and maybe the opponent is forced to concede own contradictions or rethink the statements. A bombastic spiel or slipslop shows or feigns further knowledge and propositions—and the audience may get the impression that there is still a lot to say. Eloquence, that is, a rhetorical volubility, can transfer a convincing argumentation into a convicted case, because often a refutation by words is taken as a falsification by fact.

This would be a suitable closing for the tricks for a dispute about invention projects, but Schopenhauer furnishes a very last trick: An insult, a personal hurt or rudeness about reputation will surely put an end to any oral dispute—as an ultimate mean. However, successive legal as well as physical prosecutions have to be envisaged. And this last trick may leave the platform an appropriate means for a dispute.

Scientifically, the success of eristic is based on the inherent uncertainty of all topics, which are not proved by fact. Therefore, they are undoubtedly dubious, yet open for any reasonable research, too. The purpose of eristic is a fair defense of propositions, yet fairness implies an equal knowledge about tricks for all parties and stakeholders.

A second look on the tricks may make it clear that each advantage implies a disadvantage for the opponent—and in turn the opponent could be us. At best, a mutual application of the tricks helps to deepen the understanding and harden the proposition. At worst, a permanent bossiness leads to unpopularity and isolation. Sometimes it should be enough to know the tricks, without necessarily using them. It may be a question of honesty, but human communities usually have a certain feeling for it. And perhaps, one has to be honest first to be admitted for a dispute about research options.

Lesson 30

Inventions need a controversial bossiness!

4.2.3Contradiction

To each its own.

On Duties 1, 15 by Cicero 44 BC

Inventions result generally from problems, conflicts, antitheses or contradictions, as has been already explained for development. Thus, a contradiction is a special form of correlation between a pair of intentional factors, which open a way toward inventive development. Since the previously introduced inventive principles of development by TIPS are general solutions for problems, it appears rather promising to research the contradicting factors behind about the causes for the respective problem. The general research of such metaphorical factors enables a deeper insight into inventive patterns and furnishes an approach to paradigmatic change and disruption.

By his laborious work in evaluating inventor certificates for TIPS, Altshuller derived an encyclopedic set of 39 factors, which he estimated to be the general cause for most patent claims. Hence, 39 institutions should be enough for a general research in applied sciences. While in 1620 the Lord Chancellor Bacon named just 20 research institutions, labors, and houses to cover a practical exploration of the whole world, the number of institutions for applied research counts rather by the thousands. This may be due to the necessity to interpret the research factors in a comprehensible way for each case according to their implementation and application. Although the word “factor” defines a measurable technical fact, a metaphorical comprehension is required to understand the intended invention. So, 39 factors seems a reasonably good number to start with— they are of the same magnitude as the 62 questions of Osborn’s checklist, the 40 inventive principles of TRIZ or the 38 eristic tricks by Schopenhauer. And again the handling of those factors can be facilitated by a further clustering to four superior classes.28

The first class contains six factors of mechanical causes for inventions: weight, length, area, volume, load, and energy of an object as a physical body. For example, the weight of an object causes strains, which result in momentum according to the length of the object and lead to tension according to the object’s surface area; this provokes deformation of the object’s volume until a limit of its stability is exceeded and the stored tensile energy is set free. Since the effects of mechanics differ with regard to the motion status of a physical body, that is, resting or moving, each mechanical cause counts twice, that is, by statics or by kinetics. For instance, the weight of a moving object affects its acceleration and its lever arm distance a turning moment; the area of a moving object induces flow resistance and its bulk volume is responsible for a higher rotational inertia, since the inertia of a moving object entails its stability by conservation of momentum and its energy, too. Please note that these are only general statements in order to exemplify the effects caused by measurable factors. Altogether, a total of 12 different causes by mechanics are provided by this first classification.

The second class contains ten factors to seize the remaining physical causes and their properties: velocity, force, pressure, form, robustness, elasticity, temperature, brightness, power, and substance. For example, the effects of an impact are due to velocity and, according to the impact duration, due to force and, according to the impact area, due to pressure, which all are causes from outside of an object. From inside of an object, the effects of an impact are influenced by its form, for example, globular, angular or fuzzy, and by its robustness under structural tension, as well as by its elasticity due to extension. Furthermore, the appearance of an object is physically affected by temperature, for example, softness or rigidity, or by its brightness, for example, its visibility. And finally, the general changes of an object depend on the transmitted power as well as on the amount of its substance. Again, the examples are just meant to give a first impression about possible effects due to these 10 physical causes.

The third class subsumes nine factors as cause for inventions according to the measurable effectiveness of an operation: On one side those factors are due to the consumption or loss of energy, of matter, of information or of time. For example, these four factors have to be avoided or restituted for a better effect of the invention. Then there are causes due to precision of reliability, of measurement or of reproducibility. For example, these three factors have to be enhanced to ensure a desirable effect. And finally, there are to consider actions taken on an object as well as reactions by an object. For example, these two factors are the reason for an effective functionality. Altogether, this third classification contains 9 different causes for the effectiveness of an operation.

The fourth class gathers finally the measurable efficiency of an invention with eight factors. In general, they concern the business performance by producibility, usability, reparability, adaptability, structural complexity, controllability at use, automatability or by productivity. Please note that all these 8 abilities have to be understood in a measurable way in order to claim an inventive technical effect.

All these 39 technical factors are now correlated in order to research possible inventions for an overall working system. And each apparent contradiction in this correlation should be bridged by inventive principles in order to improve a technical functionality (see Figure 4.8). This is the basic idea of a contradiction matrix, where the typical inventive principles at the intersection of two different factors are listed.

Figure 4.8: Contradictions between different technical factors (TF) become linked by particular inventive principles (IP).

Figure 4.9: A research building for contradictions with 39 interfering factors on each level and 40 levels of inventive principles—yet, not every lab is reasonably working.

Lesson 31

Inventions are spurred by contradictory aims!

4.2.4Incompleteness

To know many things does not make it for a comprehension.

statement attributed to Heraclitus by Diogenes Laertius

in: Lives of the Eminent Philosophers, Book 9, 1 about 300 AD

In the 1920s the famous mathematician Hilbert drafted a research program to complete the theories of mathematics. However, in 1931 the mathematician Gödel proved a theorem about the general incompleteness of this approach, or to use mathematical terminology: Any theory T including basic arithmetical truths and also certain truths about formal provability underlies the following statement: If T includes a statement of its own consistency, then T is inconsistent.

Consequently, the simple question of whether the mathematical logic is always consistent cannot be answered by mathematical logic, because the particular conclusion to prove the logic can hazardously be inconsistent. Hence, mathematics would be just logic, because of some illogicalness, which does not appear very logic, does it? Or, to put it positively: There are always further modalities to develop the theories of mathematics. And scientifically: There are always some categories that exceed the framework of human understanding, as already stated before.

Consequently, a technical system should similarly disclose innovative opportunities for an upgrade, because neither science is ever going to hit a dead end nor will innovations ever stop. Something can always be added, because science is always open for a new reasoning. It is rather doubtful that all scientific or inventive accomplishments can be developed within the framework of acknowledged classifications. Novel verities may turn out by research of the known due to new problems and their respective innovative solutions. This is the meaning and the merit of systematic skepticism, literally comprising appropriate doubting, due diligence, cautious survey, and prospective spying.

Toward the end of the 2nd century the philosopher Sextus Empiricus edited a summary of the methods of Pyrrhonian skepticism, that is, a Greek school or think tank founded by Pyrrhon some five hundred years before. In the beginning he states quite intelligibly how skepticism works:

Skepticism is the ability to find the opposites both of objects of experience and of objects of thought in any way whatever. Because the opposed things or reasons have equal force, we are led first to suspension of judgment, and then to serenity. I do not mean ability in any technical sense, but simply in the sense of “being able”. By objects of experience I mean things given to our senses, which is why I contrast them with objects of thought […] By opposed reason, I do not mean absolutely any assertion and its denial, but only conflicting reasons. By having equal force, I mean being equally probable and equally improbable, so that neither of two conflicting reasons is more probable than the other. Suspension of judgment is when the process of thinking comes to an end, without our denying or asserting anything. Serenity is freedom from disturbance, and calmness [101].

Afterwards Sextus Empiricus furnishes three lists containing 17 transformations in order to doubt any statements. These transformations are called tropes, literally standing for change, conversion, and transmutation, like the way tropical winds change their direction in the vicinity of the equator. Remarkably, the tropes provide a practical method to change systematically various aspects of cognition. Therefore, skepticism is a rather useful way for research, in spite of being often presumed as obstructive, delusive, irritating, and impractical. By tropical doubts a skeptic gains a vast spectrum of alternatives; and literally “skeptic” and “spectrum” are connected words, standing for “insight”, “prevision”, and “circumspection”.

Actually, these tropes still turn out to be quite useful for an investigation about research topics. In the following, 5 lists with a total of 18 tropes are presented with some updates, since a certain adaptation for the purpose of invention and innovation management is required anyhow.29

The first list of tropes contains four doubts on perception, which may therefore be changed. An impression is doubtful due to habits and aging, because by repetition sensual perceptions are sometimes sharpened or sometimes dulled, since the human sensory system reacts autonomously to the perceived intensity of light, sound, smell, taste or pain. And the sensual experience is doubtful, too, because frequent use of machines, cars, videos or computers changes the feel for distance, velocity, time, and load, since there are differences between real and virtual experiences, that is, by day or by dream. Then, the range of a sensed expertise is doubtful because manned and unmanned vehicles and instruments report experience far beyond human perceptibility, for example, from ocean grounds, outer space objects, microbial life, molecular structures, and high-temperature processes—however, there are still considerable differences between personal sensations and instrumented inspections. Finally, the general concept of perception is somehow doubtful, because it interferes with the actual view about space, time, economy, and society, for example, by wave-particle duality and quantum leaps in mechanics or space warp and time dilatation in relativity theory or humanistic, liberal, capitalistic, and social ideologies for the cohabitation of people and political systems.

The second list of tropes contains four more doubts of reality with regard to the uniqueness of appearance. An appearance of a material can be quite different when it achieves comparable effects, for example, metals nowadays substitute stones and bones—and plastic substitutes natural materials like wood, wool or silk—and semiconductors substitute relays and increasingly data processing devices, formerly preserved for the neural network of a human brain. Then the form of objects can be quite different, too, for example, by granular, fibrous, plane, porous or micro-structured bodies, like the texture of steel alloys, or by the fiber reinforcement of composites or by the multilayering of concealments or by the porosity of absorbers. Further, the amount of objects can cause a different effect within a mixture, for example, the doping of semiconductors or the dosage of medicine, the efficiency of foams or fogs and the metered addition of technical agents in the right moment. Finally, the purpose of objects can be deliberately altered by reassignment, for example, a piece of charcoal can serve for a fire or for a drawing or for steel hardening or for filtration of air and water or to gain dispersed resources. Especially water seems to be the most alterable matter of the universe, enabling the manifold of biological existences.

The third list of tropes contains another set of four doubts on judgments. According to Kant’s categories for judgments mentioned before, the quality of a constitution can differ by another distribution, for example, a single bee appears less threatening than a hive, a grain of sand is less impressive than a desert and a regular sponsoring is less exhilarating than an unexpected gift of the same amount. Then, the quantity of a constitution can differ when compared to another perspective, for example, the hostile temperatures of the sun, on one side, permit a convenient ambiance for life on earth, on the other side—and compared to a mite a microbe is minuscule but responsible for worldwide plagues—a single dollar will increase at 10% interests to a thousand within 49 years—and a written contract comprises more than a mutual handshake. Further, the relations within a constitution can undergo different interactions, for example, red hair and blue eyes result simply by black and brown pigments interacting with the white stroma—and inert titanium dioxide becomes a catalyst for chemical reactions by ultraviolet radiation—and there is obviously a difference if one meets personal friends or a group of strangers. Finally, the modalities of a constitution can differ due to the circumstances, for example, a thimble of benzene is enough for a lighter, but not for a car—and a tip of thousand dollar is excessive, but not enough as a month salary—an island may prove to be a joyful holiday spot or become a nightmare if one is a castaway there.

The fourth list of tropes is due to four doubts in regard to reason as a confirmation of knowledge: A technical fact may get another significance according to the linguistic usage, for example, recycling means literally a repeated reuse of technical products, which may concern the product itself by repair, or just the restoration of similar products with the construction material, or merely the recovery of the raw material, or even only the dumping of materials to refill the excavations in nature. Then, the psychical reason may get other explanations according to the employment of metaphors, for example, an apple is a round edible fruit from trees, but this holds true for a comparison with oranges, peaches, pears, and prunes as well—and people are free like birds in the sky, which seems yet not enough to seize the particularity of human freedom—and electrons orbit the atomic nucleus like planets the sun, which is nevertheless inept to understand quantum leaps. Further, a logical justification may obtain other validity by exceptions, for example, people with similar habits have an equally similar life expectancy, unless influenced by genes, height, life story, education, and so forth—and bodies usually fall to the ground, unless they are lighter than air or tracked up by invisible forces. Finally, a casual coincidence may gain other importance by discovery, for example, all swans have been white, until a black species was discovered in Australia—and time appears as a universal dimension, until a dilatation was discovered as well for the rotation of Mercury, as for the half-life of cosmic mesons and as for an atomic clock inside an aircraft flying around the globe in 1971 [102]. In general, it is not mandatory that a part represents the whole, neither does a correlation hold true for all cases nor a conclusion arbitrarily applicable, and a comprehension is not valid forever.

In the end, even science itself underlies two possible changes according to its two canonical truths. On one side, the deduction may be doubted according to the hermeneutical validity. For example, energy is theoretically a property, which stays constant by variation of the general equation of motion. Hence, the conservation of energy is a conclusion of this approach and not a heuristic finding, anymore. However, by the uncertainty of quantum mechanics a general equation of motion is never feasible and the conservation of energy can be resolved within the limits of Planck’s action quantum, that is, an appropriate short time. This explains the quantum tunnel effect—and by the Copenhagen interpretation each theory is just a model, which holds true as far as its deductions coincide with real effects.

On the other side, the induction of a reason may be doubted according the heuristic generalization of experiences. For example, the practical definition of a mass is the proportion between force and acceleration of a body. The value of a mass is therefore fixed by heuristics and can never achieve another value. However, the speed of light is a limit for all movements, and consequently more acceleration does not increase the velocity of objects, anymore. In the relativistic theory the mass does therefore increase, and at high velocities a distinction of mass at rest and moving mass is introduced.

In general, the purpose of research is to overcome paradigmatic limitations. Today, if we ask for objectivity and impartiality in science, we genuinely comprise a considerable skepticism. This means, for instance, an appropriate mastery of science in general and of scientific disciplines in particular and also an appropriate reference to realistic facts proved by comprehensible reasoning. Furthermore, this includes an appropriate analytic discussion of problems in order to realize, state, name, and discern contradicting oppositions. And finally, it comprises an appropriate indifference in regard to the solution in order to achieve a best opportunity. Indifference does not mean an adventurous and dreamy hope to arrive somewhere; indifference corresponds primordially with the hard work to excavate a concrete utopia and the principle of hope. And each of the tropes represents an approach to turn a hopeless commitment into a hopeful project with probably innovative achievements.

Lesson 32

Doubts can cause an inventive change!

4.3Prognosis

Prediction is very difficult,

especially about the future.

saying attributed to the atomic physicist Niels Bohr 1885–1962

According to recent discoveries in neuroscience, a major part of the human brain is permanently concerned with a prognosis, literally meaning a precognition of events in the future. However, these considerations are mostly subconscious and just predict how our footsteps have to be placed when walking a uneven path, how an object is moving and how to coordinate our own movements to get it or to evade it, how to respond appropriately to an argument and how to prepare an understandable articulation in due time.

As the processing of sensual information input requires at least about one tenth of a second, our considerations are permanently running ahead of our actions in order to keep up with eventualities. And if there is a necessity or some spare time for considerations, this ability to derive preparatory knowledge can be extended—even in a conscious way.

In 1814 the scientist Laplace described a notion about the inability of the human wit to predict the future correctly, because for this purpose a supernatural intellect would be required called Laplace’s demon:

An intellect, which at a certain moment would know all forces that set nature in motion, and all positions of all items of which nature is composed, if this intellect were also vast enough to submit these data to analysis, it would embrace in a single formula the movements of the greatest bodies of the universe and those of the tiniest atom; for such an intellect nothing would be uncertain and the future just like the past would be present before its eyes. [103]

Consequently, any surprise by inventions, projects and innovations would then be impossible or obsolete—one could add with certain affirmation. If reliable prognosis would be achievable, the final state of destiny would become feasible as well, without further necessity for economy, improvement, disruption or any kind of management.

Scientifically, inventions and innovations are not yet real and have to be realized in the future. Consequently, a particular research concerns the prediction of the future in order to anticipate the future problems and to work on their solution in time. At least, the opportunities of a development or a research can be estimated by a prognosis of the future. However, a prognosis or precognition of the future is not scientific in the general meaning, because scientific knowledge is about admitted truths—and not about suppositions. All statements about science can just be verified when they already exist. And non-existing things do not provide a factual truth or a valid reason.

But, considering all the knowledge that humanity has gathered in modern sciences, it appears feasible to estimate reasonable causes for probable facts in a justifiable way. In this sense, predictions depend on logical agreement, which epistemologically corresponds mainly to some justification.

Hence, a prognosis is obtained completely suspended from both, that is, factual as well as reasonable truths—made up out of thin air, as can be stated truthfully (see Figure 4.10). Thereby, predictions are less true than research and much lesser than development, because a logical conclusion is either right or wrong, yet never true alone, as already explained for the research of falsifications earlier. And therefore, a truly infinite amount of logically sound statements about inventions, patents or innovations can be derived, yet not verified. This is a novel aspect of inventions and the corresponding innovation management.

The lack of an appropriate amount of knowledge is a principal barrier for people to predict the future. And often one calls a scientific expert to make a prospective statement, because he or she is accredited with more skills. However, a true scientist usually is aware about the elenctic barrier as well as the incompleteness in science and therefore generally refuses to take any responsibility for such speculations. Perhaps, serious and renowned scientists are not really the perfect choice for innovation managers in general.

But at the beginning of the 20th century a fundamental problem appeared for the basic understanding of the physical verification of elementary particles. The previously mentioned uncertainty obliges even the physicists to describe the factual state of a quantum object in any case with a certain variance δe, where δ is the uncertainty

Figure 4.10: A prognosis is just a logical justification suspended from facts and reason. for a factual event e. And in quantum mechanics the factual appearance of an event E is derived from the probabilities p(e) of all events by integration of the tested spread from a to b:

However, by any real experiment Ei it is just possible to observe single or discrete events by the number i of repeated trials. As all the experiments a person can perform in a lifetime is limited, even the effort of a hardworking experimenter is finally restricted to a general survey making

with i = 1 . . . n, as the highest integer number of experimental tests.

The total experience EG is everything, what can be seriously known about an event. In fact, the probability for the occurrence of a novel kind of event decreases according to the number of experiments already performed. Yet, according to the given general uncertainty, the probability will never vanish to zero. Consequently, within the extended interval from minus to plus infinity, even the smallest probability p(e) will contribute to a further exceptional event. Hence, in regard to any amount of limited experiences EG it is mathematically:

In other words: Although the experienced discrete events are much more probable than all other events alone, a continuum of all the other events may become more probable than all limited experience. Or, in simpler words: Sometimes anything unexpected will surely happen. What we know is a droplet, what we ignore is an ocean—as Newton is said to have stated (see Figure 4.11).

However, the application of scientific knowledge is quite reliable to repeat a technical performance with a sheer endless number of times, for instance by the repeated propulsion strokes of an engine or by the production rate in printing or in machining fabrication. We all trust constantly and permanently in uncountable cases—and with great success—on scientifically reliable knowledge about mechanics, thermodynamics, electrodynamics, and optics. Maybe, with nuclear physics a certain limit has been reached, in regard to the reliability in secured operation. But modern technology relies on predictable engineering by the knowledge of physics, chemistry, biology, economics, management, and many others—why not of inventions and innovations, too?

There are even some scientific considerations on how to obtain a limited output by an infinite input. In the number theory of mathematics there are infinite series that approach infinity like the infinite sum

But there are other series that converge to discrete number, like the infinite sum

And there are even series that attain a new kind of transcendental number, beyond all the number of all fractions, like the infinite sum

where e is the Euler’s number 2.7128182845904523536 . . . .

Obviously, an infinite input does not always yield an infinite output.

For instance, the kinematic task to move from A to B can be split up in infinite intersections, which are yet crossed in a finite time—and actually this has been one of the classical paradoxes of motion described by the Pythagorean philosopher Zeno.

Another example was brought up by the astronomer Olbers in 1826 about the limitations of the universe: If the universe is infinite, then at each point of the firmament there should be a star somewhere to bright it up—and consequently, the night sky would be bright. Obviously, there has to be a certain convergence of the universe to explain the dark sky at night [104].

This principle of convergence has to be transferred to prognosis in order to anticipate scientific and technological research and developments. If we assume that a sufficient scientific knowledge about innovation projects and about their marketing as well as the development and the research of inventions is given, then it should be possible to derive justifiable predictions about the future. We do not know exactly the extent of verity of this kind of anticipation; yet, we know that there is some logic correlation when the sequence of successive assumptions converges.

Figure 4.11: Distribution of single events E above the possibilities e—according to their respective probabilities p.

Lesson 33

Algorithms are the main tool to derive inventive predictions!

4.3.1Prophecy

Know thyself.

Inscription at the Temple of Apollo at Delphi 6th century BC–4th century AD

Coins were invented in the 6th century BC in the Greek kingdom Lydia, Asia Minor, nowadays the western part of Turkey. In consequence, its sovereigns became fabulously rich and King Croesus could afford to test—by means of generous offerings— seven different oracles about their abilities for correct prophecy—literally meaning prediction. Thereby the Delphic Sibyl at central Greece was able to give the right answer about Croesus’s meal on a particular day, which was turtle with lamb cooked in a brazen pot. Soon, Delphi became the most renowned oracle of the ancient time until its prohibition in 391 AD by the Roman emperor Theodosius I.

Although the secret of the Delphic Sibyl is still quite obscure, her predictions are known to be insinuated and/ or interpreted by the local priests of Apollo, a Greek god who mythically slaughtered the visionary snake Python at this place. The site of the temple was also renowned as the navel of the Hellenic world and many trade routes crossed by this central point. Since it was rather remunerative to run an oracle, many priests and temple servants were appointed to gather useful rumors, draw suitable conclusions and elaborate a convincingly mysterious prophecy. Additionally, one may interpret the maxim “know thyself” of the Delphic temple as a forecasting by self-awareness, that is, all the uncertain inner feelings and personal impressions bear on a hidden verity, which will turn out often to be true on an average.

In 1963 the American research and development corporation RAND framed a procedure called Delphi Method in order to derive stochastic expertise from disperse knowledge. It depends equally on the assumption that each individual can be credited with a particular personal experience and expertise—to a certain degree, at least. Sure enough, experts have considerably higher experience than laymen, and they may be especially experienced with rather seldom or remote peculiarities of a topic. Hence, their statement can be estimated as more evasive, cautious, and balanced, in general. In contrast, laymen will surely provide a larger spread of estimations and comprise less justification by facts and reason. But a great number of laymen may gather a larger collective expertise than an expert in a lifetime—at least, if the topic is somehow perceptible and comprehensible to everybody.

For example, in 1906 the British natural scientist Galton visited a farm animal fairy, where an ox was promised as reward to whoever could estimate its weight the closest. Surprisingly, it turned out that the average of 787 estimations was less than one percent to the precise value—and thereby closer than all other single estimations, including those of experts like butchers and cattle dealers. In 2004 the American journalist Surowiecki coined for such stochastic phenomena the term “Wisdom of Crowds” [105]. Referring to this, the Delphi effect is based on a clever way to combine expertise of numerous people who are appropriately familiar with the topic. This effect can be ensured by four characteristics as follows:

First, any estimation has to be independent from other opinions. For it seems quite useless to ask several people who have already agreed to a certain judgment. Their expertise may get higher weightage and perhaps succeed but their individual distinctions are surely uniform and will cover the possible options only in a minor extent. There is proof for an opposite of the wisdom of crowds, if people interact prior to a decision. This is known as cognitive biases according to stereotypes, framing, hindsight, endowment, anchoring, and many others. In this sense, it would be much easier to ask repeatedly a single expert alone, which would then save some efforts and provide a similar result [106].

Second, the number of expertise has to be significant due to the complexity of the estimation. For it appears equally strange to ask only a few friends, maybe of a similar age and comparable lifestyles. Their estimations will again be reasonably close with a limited spread. This sort of convenience sampling produces merely representative results for the experience of a peer group. Again, it would be rather comfortable and equally relevant to organize a simple interview and just recapitulate the general impression afterwards.

Third, each expertise has to be reconsidered and reassessed by a second guess. For the first guess may be just a spontaneous response without any true consideration of facts and reason. Each person may arguably vary a decision to a certain extent and hazardously the resulting deviations may superimpose disadvantageously. By getting informed of the provisional mean value and the related distribution, a participant of a poll has a reference to make a second guess. As a consequence, unfounded deviations from the mean get lowered and founded deviations get enhanced, because an inferior self-assurance will converge to the mean and a superior self-assurance will be more distinct. Altogether, the algorithm for the method will be more pronounced.

Fourth, the repeated estimation is only feasible by anonymous evaluation, that is, a statistical analysis. There is a given danger that serious decisions are prohibited by personal vindication. Experts, in particular, are known to defend a primary statement—if necessary by resorting to eristic techniques of permanent uncertainty as described before. Anonymity provides the opportunity to change a previous estimation honestly, without a loss of face. Nevertheless, it is disputable, because jokers and tricksters may misuse the opportunity to spur their own interests. And this can thwart the Delphi method in general.

A Delphi study comprises also a process of opinion formation, which is anyway a surplus of the process. Although it seems rather tempting to affect the result by covert agreements—especially if desired research funding or innovation projects come into the play—a shared opinion is already a win for subsequent joint activities. Indeed, it is often asked to prevent conflicts of interests by excluding experts from such a study. But practically the impact of experts becomes insignificant by a suitable amount of participants. And their contributions are sought anyhow for further specifications. In the end, general opinion is supported by public attention, creditable knowledge, and individual empowerment—and this effect of a Delphi study is often underestimated.

Accordingly, the entelechy of a Delphi study can be divided into the following four stages:

In the beginning a set of topics to be forecast is needed as well as a significant number of people who have some experience with these topics—for instance, a collection of subjects, which are controversially discussed in public or by professional circles. Only if a sufficient amount of people feel involved can one count on enough experience and participation for a campaign.

Then, a selection of eligible choices has to be established for each topic because just a concrete statement is apt for statistical evaluation. For instance, a query about the prospected year or the degree of maturity can be averaged as well as a specific decision between several options. But an unspecific question about who, what, where, why and how would just result in manifold statements without particular meanings. According to the required number of anonymous participants of the study, an accumulation of estimations is mandatory for the statistical evaluation. In order to prevent later misinterpretations it is advisable to furnish an eligible choice.

Afterwards, the experts are invited for a first guess with a subsequent statistical evaluation. For instance, the numerical mean value and the median are calculated as well as the standard deviation and the total spread of the responses. A difference between the mean value and the median indicates whether the distribution is symmetric or asymmetric. The standard deviation is a measure to comprise the majority of estimations by the point of inflection of a distribution. And the spread provides a number for the total difference of all estimations. With these statistical values everybody should be able to rate the own opinion in regard to the general dictum.

Finally, a repetition of the same inquiry seeks for some convergence of this algorithm. For instance, it is advisable to explain first and then repeatedly the principle of anonymity and to insist just as well on sincere participation. Since the task of data processing is meanwhile largely facilitated by electronic spreadsheet analysis and interactive communication devices, the main challenge for the poll is the correct questioning and patient inquiry for feedback. Although the response may appear clear enough, a larger timeframe has to be considered to comply with all the possible demands of the experts. Nonetheless, even a certain diplomatic skill is required to obtain the desired support.

In general, a Delphi study is based on a self-reflective effect, which is realized by a method of questioning. The result of such a study is both a collective prediction and mainly an agreed opinion.

Lesson 34

The casting of opinions is a step toward inventive perspectives!

4.3.2Anticipation

The best way to predict the future is to create it.

saying attributed to the management pioneer Peter Drucker 1909–2005

If one wants to move from one place to another in due time, there are mainly two alternatives for an orientation: One is navigation by indication of the direction to take, maybe accompanied with information about the distance to the destination and perhaps advices about appropriate speed. This is the operational mode of electronic route guidance systems and is quite efficient. It seems to be enough to know which exit to take and how long to drive with a given speed, if the next stop is quite close or just straight ahead. However, if the destination is reachable by several paths with varying opportunities, then it is advisable to refer first to a map in order to anticipate probable occurrences.

For example, one way may be the shortest but time consuming, another is perhaps longer but considerably faster, and another again is perhaps safer by giving some recreation stations and landmarks for orientation– and a further one is narrow with unexpected changes or detours, yet quite picturesque. By a precursory comparison of the possible pathways and their respective features a suitable choice can be elaborated and discussed for the best pick.

Similarly, futurity can be expressed at least in two ways, too: The first is the common prospective way about eventualities, which will occur in the future. This corresponds to the predictive prophecies mentioned before. The second is the more seldom used way of accomplished visions, which will be given in the future. While prognoses of the first way are somewhat simple predictions about how things are going to be, the second way comprises a perfect statement about the future situation and presumes further consequences of this status.

For example, improvements are generally innovations in simple future, that is, an invention “will be” on the market. Everybody understands this as an intention to pursue a prescribed way, but not yet its accomplishment. Maybe the introduction to the market has to be delayed or the concept of the invention has to be adapted according to change requests of the customers. Maybe the concept of a project turns out to be unrealistic, its organization unfeasible, its planning unachievable or its controlling out of time or budgeted costs. Maybe there are other approaches serving the same purpose and preventing a due specification by exploration, feasibility, prototype testing, and launch. A simple future contains obviously many uncertainties and room for changes, counteractions and alternatives to adapt the inventive intention.

In contrary, disruptions are mostly innovations in future perfect, that is, the anticipation of an invention as “will have been” on the market. Everybody understands this as an imaginary set of a finished project case. The result is presumed as delivered and further consequences are already derived. Maybe a secondary project after the launch of a primary project will be envisaged—or prospected earnings in the future will already be taken into account by means of a Net Present Value, as mentioned before. Maybe strategic investments will be anticipated and further “will-be” innovations are already included in the considerations. For instance, if all the existing machinery will have been equipped with electronic sensor and control devices within a computational network, then another disruptive change in industry will happen by Cyber Physical Systems (CPS). Especially a disruption depends on revolutionary consequences for the case of its introduction on the market. And future perfect describes an inevitable virtual situation in order to think one or several steps ahead.

In mechanics, the kinematic motion of bodies can be depicted mechanically by path lines and by timelines. A path line represents the way an object takes from one point in space to another. However, the motion by time, velocity or acceleration cannot be shown in this way. For instance, a long-time exposure of head and rear lights at night shows the ways cars have taken—yet it contains no perceptible indications about time, velocity, and acceleration. But if a path line is just straight ahead, the spatial dimension can be depicted on one axis of a diagram, leaving place to show a timeline on the axis perpendicular to it.30

Timelines and path lines depict the places of an object on its path at different time sets (see Figure 4.12). By linear interpolation the respective status of motion can be approached with the differentiation quotient. The representation of path lines for stationary movements look quite similar to timelines and are commonly used as matter of course, although containing different information. A factual map of roads is just suitable to depict path lines by itinerary points, stations, and landmarks on the route in space. But an innovation roadmap has to provide additional information about time in order to derive the related timelines perpendicular to a path.

Innovation projects or programs can be depicted by a roadmap in order to support the compilation of an algorithm for a successful project. Therefore the respective path lines are divided into several prospective sections of time. The timelines are perpendicular to the path lines and help to elaborate and compare the progress. In general, the road consists of several tracks serving different fields of interests, for example, business fields, technologies, or environmental aspects. Interstations on such a roadmap are related inventions and their successive diffusion as innovations, for example, introduction on the market and the subsequent stages of growth, of maturity and of saturation, as previously described for the typical changes in innovation marketing. Hence, a prospective grid is obtained for an analysis and for a synthesis of interactions and strategies.

Figure 4.12: A roadmap for several innovations on four path line tracks with three timeline milestones.