Rickerism

“And from the book, as his fingers stroked, a voice sang, a soft ancient voice, which told tales of when the sea was red steam on the shore and ancient men had carried clouds of insects and electric spiders into battle.” Ray Bradbury, The Martian Chronicles

“The art of war is subjected to many modifications by industrial and scientific progress. But one thing does not change: the heart of man.” Colonel du Picq, 1869

Forward

The intentional destruction of cooperation between individuals is the most direct means of victory. Information warfare is the implementation of this theory.

Many authors have focused on the symptoms of information technology without proposing a theory that can explain and predict success in warfare. The effort so far in identifying, grouping and naming applications of information technology in war has formed taxonomy but not a theory. Taxonomy is nothing more than a hierarchy for structuring scientific analysis. We create taxonomy of species to analyze plant and animal life, taxonomy for chemicals, languages and so forth. Taxonomy will not explain and predict success. For instance, one could create an exhaustive taxonomy of bridges, but merely classifying a bridge would not explain why certain bridges stand up or predict what new bridge designs might stand up. In order to explain and predict success, one would require the theory of vector mechanics.

Some authors have written about particular information technology such as network security and software viruses and how to employ these technologies in war. Others have written about trends in information technology development. For information warfare, we must step beyond taxonomy and examples to theory. A theory is the distillation of experience and reason that can explain and predict success. Frederick the Great taught his officers that,

“Theory facilitates practice. The lifetime of one man is not sufficiently long enough to enable him to acquire perfect knowledge and experience; theory helps to supplement it; it provides a youth with early experience and makes him skillful also through the mistakes of others.” [1]

This theory of information warfare states that the destruction of cooperation between individuals is the most direct means of victory. It explains success: efforts that target the destruction of means of cooperation will achieve victory more effectively than the destruction of other targets. It also predicts success: if destroying particular facilities, equipment or even individuals destroys cooperation between individuals, then it should be targeted before others.

It may strike the reader that the theory makes no mention of information technology. For the theory to be fundamentally true, it must always have been true. The advent of information technology has not changed any fundamental truths. It has merely brought certain truths into much sharper focus, brought their impact to the forefront of our attention. A similar situation occurred at the first half of the last century with mechanization. Liddell Hart, Fuller, Guderian and others argued that maneuver and the indirect approach had always been true. To explain the importance of maneuver, these men used examples from previous wars in which there were no mechanized forces. Tanks and related mechanized technology only brought the importance of maneuver and the indirect approach to the forefront of our attention.

The implications of information technology should be addressed in theory rather than taxonomy. In order to fully explain this theory of information warfare, we will need to provided several supporting theories, namely the theory of information technology, the theory of automation, the theory of information and the theory of cooperation. Since it is information technology that has brought such issues to the forefront of our attention, we shall begin with the theory of information technology.

Introduction

In the introduction to his fundamental work in computation science, Marvin Minsky wrote,

“By abstracting out only what amount to questions about the logical consequences of certain kinds of cause-effect relations, we can concentrate our attention sharply on a few fundamental matters. Once we have grasped these, we can bring back to the practical world this understanding, which we could never obtain while immersed in inessential detail and distraction.” [1]

We will take Minsky’s advice to heart and attempt to reduce information technology to a few fundamental matters.

Information technology is actually two technologies, electromagnetic communication and the digital computer. James Maxwell made electromagnetic communication possible through his four field equations. Alan Turing made the digital computer possible through his mathematical theory now called the Turing machine.

All that we call information technology is but combinations of instances of employing the Maxwell equations and the Turing machine. The possibility and limitation of all information technology rests in these two theories. Information technology is capable of achieving everything that is theoretically possible through Maxwell’s equations and Turing’s machine. Likewise, information technology cannot achieve anything that is theoretically impossible. An understanding of these two theories will enable us to understand why they are changing the conduct of warfare and what the inherent limitation of that change is. Our eventual objective is to be able to make fundamental conclusions for the impact of information technology in warfare as JFC Fuller and others did for mechanization.

Turing’s machine

In 1936, the British mathematician Alan Turing published a paper entitled “On Computable Numbers, with an Application to the Entscheidungsproblem”.[2] The Entsheidungsproblem, or “halting problem”, was presented by the German mathematician David Hilbert in 1900 and more clearly defined in 1928. The question was: “is there some general mechanical procedure which could, in principle, solve all the problems in mathematics (belonging to some suitably well-defined class) one after another?”[3]

In his paper, Turing described an imaginary machine, a black box with an infinite tape. The tape is divided into squares, each square either containing a mark or blank. The input to the machine is on the tape to one side of the machine and the output is on the other. The machine contains within it a finite state, that is, some finite number that is assumed to always begin as zero. The machine has the ability to

1. read whether the immediate square is marked or unmarked,
2. change its internal state based upon the existing state and whether the tape is read marked or unmarked,
3. write or erase a mark on the immediate square, and
4. move the tape left, right or stop.

Except for the infinite tape, such a machine is very conceivable to us. Inside of the machine is a simple table of finite length. The table holds simple instructions. One instruction in the table could be: if the internal state is 17 and the square read is marked, then change the internal state to 25, erase the mark and move the tape right.

Figure 1 The Turing machine is an imaginary black box that reads and writes marks to an infinite tape

Turing’s paper was a giant breakthrough that “contains, in essence, the invention of the modern computer and some of the programming techniques that accompanied it.”[4] John von Neumann built the first electronic digital computer based on this paper in 1945.[5]

It should be noted that computing machines date much earlier than von Neumann’s efforts. Babbage created a calculator using clock gears. Archaeologists have uncovered complex machines from ancient Greece. The differences are that von Neumann created a universal machine using electromagnetism rather than a dedicated machine using mechanics. Without employing electromagnetism, it would be impractical to build a Turing machine of enough complexity to be useful.

Algorithms

To understand the inherent limitations and capabilities of the Turing machine, we must first understand the concept of the algorithm.

“The concept of algorithm is one of the basic concepts of mathematics. By an algorithm is meant a list of instructions specifying a sequence of operations that will give the answer to any problem of a given type. Of course, this is not a precise mathematical definition of the term, but it gives the sense of such a definition. It reflects the concept of the algorithm which arose naturally and has been used in mathematics since ancient times.” [6]

The concept of the algorithm is the essence of the digital computer. Most of us are taught Euclid’s algorithm, a sequence of operations for finding the greatest common divisor of two numbers. The algorithm can be expressed as follows:

1. Given two positive integers, a and b,
2. If a is equal to b then stop, the answer is b, else
3. If a is less than b then swap the numbers so that a is greater than b
4. Divide a by b and let c be the remainder
5. If c is zero, then the answer is b, else
6. Set a equal to b and b equal to c
7. Repeat the sequence

Anyone with basic skills of arithmetic should be able to execute this sequence of operations. Euclid’s algorithm is the definitive example of an algorithm.[7] In attempting to solve the Entsheidungsproblem, the Turing machine provided an exact definition of algorithm.[8] Theoretically, the Turing machine can execute any algorithm. As a corollary, we can state that an algorithm is anything that can theoretically be executed by a Turing machine.

Understanding algorithms is important to understand the role of machines on the battlefield. By understanding Sir Isaac Newton’s equations of gravity, one understands the fundamental concepts of launching a rocket. In the same manner, by understanding the general concept of the Turing machine, one understands the fundamental concept of the digital computer. The mathematics of Newton’s equations itself shows us the existence of an escape velocity and stable orbit. Likewise, the mathematics of Turing’s machine shows us the existence of some very relevant phenomena.

Strong and weak AI

Most readers have heard the term artificial intelligence. It conjures up images of robots and giant electronic brains. The precise definition of artificial intelligence is difficult to establish, in part because it is a moving target. Things that were once the realm of artificial intelligence, such as daemons and heuristics, are now a part of every day computing. To address this predicament, Professor Bill Buckles[9], who taught me artificial intelligence, defined it as follows:

Consider a circle as representing the realm of all the things that we know we are able to do with computers today. Now consider a larger concentric circle as the realm of all the things that are conceivably possible with computers. The difference between the two circles is the realm of artificial intelligence. The two circles are constantly expanding outward so that the area previously considered AI is consumed by the possible while AI expands into new area.

There are two camps in artificial intelligence (AI). One camp, called strong AI, believes that human thought is simply the carrying out of some well-defined sequence of operations, that is, algorithms.[10] In strong AI, humans and digital computers are instances of the same thing. It is only a matter of time before digital computers become complex enough to equal or surpass human capability.

The opposing camp, called weak AI for lack of a better term, believes that human intelligence is somehow fundamentally different than digital computers. Their arguments rest with the theory of the Turing machine itself. I will review three of the most notable proofs of weak AI.

John Searle raised one of the more notable arguments, named the Chinese Room, which makes the case that the successful execution of an algorithm “does not in itself imply that understanding has taken place.”[11]

In 1931 at the age of 25, Kurt Gödel published a mathematical paper that demonstrated that a set of axioms could be either complete or consistent, but not both. To be complete, the set of axioms could prove or disprove any given premise. To be consistent, the set axioms would never prove and disprove the same premise.[12] Roger Penrose used Gödel’s Proof in a fundamental argument against strong AI. Penrose proved that Hilbert’s Entsheidungsproblem, the problem the Turing machine was design to solve, has no solution.[13] His discussion leads us through a number of things that the human mind deals with that are not algorithmic.

Aho and Ullman present much simpler argument. Using Russell’s Paradox, which defines a set that could not possibly exist, they have demonstrated that there is no algorithm for determining whether or not something is an algorithm.[14]

In summary, there is no algorithm for creating or understanding algorithms. Digital computers can only execute algorithms, but humans can not only create but understand algorithms. As such, there is a fundamental difference between human intelligence and digital computers.

Man, not machines, will always dominate the battlefield for two reasons. First, the machines cannot create; they can only do what their creators have told them to do. However clever the inventor, the machine must exist without its creator. As such, there will always be a man to oppose the machine that can create a means of defeating the machine. The machine is helpless to defend itself because the machine cannot create a response to a new, novel threat. The mind of man, however, is particularly adept at not only overcoming but also devising new and novel threats.

Second, and less definitive, war is a contest of wills. A machine does not possess a will, an automated conscience to create a state of the physical universe to match an envisioned state the machine has created. As such, men will not be intimidated by machines. They cannot be conquered by machines. They can be killed by machines, true, but they can never surrender their will to a machine.

Maxwell’s equations

The modern digital computer implements the Turing machine using electronics, but the Turing’s machine has no inherent dependence of electronics or electromagnetism. That is, the theoretical capabilities and limitations of the Turing machine exist independent of the capabilities and limitations of the electromagnetic spectrum. Turing machines could conceivably be constructed out of mechanical parts using fluid pressure or even out of molecular biological components. We have found it practical, however, to implement Turing machines using electronics. Electronics are dependent upon Maxwell’s equations. Thus digital computers are limited by the capabilities of electromagnetism not because of theory of the Turing machine, but because of the particular implementation of that theory.

James Maxwell developed his four field equations in the 1860s. Together they form the theory of electromagnetic fields by which man commands the electromagnetic spectrum. The electrical engineer is taught, “These equations presumably describe all electromagnetic phenomena, except for quantum modifications in the atomic domain.”[15] Maxwell’s equations were built upon and include Coulomb’s Law (1785), Ampère’s Law (1822), Faraday’s Law (1831), and Kirchhoff’s Law (1848). Maxwell expressed all these physical phenomena in pure mathematics.

Figure 2 Maxwell’s equations presumably describe all electromagnetic phenomena

What is most amazing about these equations is their simple beauty an elegance.

Prior to Maxwell, physicists were obsessed with finding what they called the ether, an invisible physical medium through which electricity and magnetism passed. Maxwell’s theory dispelled the notion of the ether and further predicted the existence of electromagnetic waves that could pass through a vacuum at the speed of light. Marconi demonstrated the radio in 1895.

There are two primary impacts of Maxwell’s equations. First, they enable individuals to communicate and thereby cooperate through a vacuum at the speed of light. We will discuss this impact further in the theory of information. Second, the equations make building a Turing machine a practical endeavor, which we will address next.

Finite limits to automation

The progress of automation is infinite, but that does not mean that the progress is without boundaries or limitations. There are an infinite number of irrational numbers between the integers 1 and 2. The limitations of the Turing machine define the boundaries of automation. There can be no Turing machine that invents new Turing machines. The Information Age is still the Machine Age, and in this age, to create is the role of man; to execute is the role of machines. This truth cannot be forgotten when planning the army or the fleet.

Theory of information

Humans are ever changing the state of the environment in which they exist. To draw from John Locke’s classic example, a man finds an apple tree in nature; he picks an apple, and in so doing, removes that apple from a state of nature. The mind possesses an image of the state of the environment, as it exists. From that image, the mind creates an image of the state of the environment, as it could exist. The mind affects the actions of the body to change the state of the environment to match the image created in the mind. The man sees the apple on the apple tree. In his mind, he pictures the apple picked from the tree and in his hand. He then proceeds to change the environment to match his thought. He picks the apple. Our survival actually depends on our efforts to constantly change our environment to meet our needs of sustenance.

Sometimes the state of the environment that the human mind envisions cannot be achieved by the direct capabilities of the human body. For instance, a man may want to pick an apple that he cannot reach. The mind can create incremental changes in the environment to achieve the desired state. For instance, the man might pick up a stick and knock the apple loose that he cannot reach directly with his hand. The stick has become a tool. Incremental changes can be used to achieve a long chain of intermediate states. A rock is used to break off a branch to form the stick to knock down the apple that could not be reached.

When humans find themselves carrying out some well-defined sequence of operations with the tools to solve a particular set of problems, the tools are combined to form machines. A well-defined sequence of operations to solve a particular set of problems is an algorithm. Machines can be thought of as physical manifestations of algorithms. The mind creates these machines or algorithms to change the state of nature to match its intent.

Picture a water mill or a windmill. The fluid pushes against the paddles. The paddles are arranged around an axel. The motion of the axel is translated 90 degrees to a grinding wheel that grinds the corn. It is a nontrivial machine. It originated with someone smashing grain between two rocks, an act you can observe in primitive areas today. A human mind envisioned an end state of nature, ground corn, an incrementally combined tools to achieve a more efficient state of nature to suit his needs. First he pounded corn. Then he ground the corn. Then he ground the corn in a circular motion. Then he attached an arm or lever to the stone to get more force from his efforts. Then he fixed an ox to the lever to grind the corn for him. Then he harnessed water and eventually the wind. Each step of the process an incremental change made by the human mind on the physical environment.

Consider that grinding corn is but a part of a larger process of baking bread. Today, large tractors plow, sow and reap the grain. Large factories process the corn into complete packaged bread mix. People pour the mix into automated bread machines in their homes, programmed to bake during the night.

Machines are combined to make more complex machines. The sophistication of the machines enables them to handle larger sets of problems. The combination of machines, the increase of complexity and the expansion of scope come to their logical conclusion with the digital computer. The digital computer is a machine that can theoretically handle any algorithm. The digital computer is the machine of machines. The mass of the complexity of such a general machine could never be achieved in any practical matter, however, without the ability to build the machines using magnetism and electricity.

Information and communication

Sometimes the envision state of nature cannot be achieved by the sole physical exertions of the individual who has envisioned it. The individual must solicit the efforts of other individuals. How does he go about doing this? How does he get the actions of other individuals to combine towards changing the state of the environment to match what he has created in his mind? He must some how transfer the image of the intended state of the environment from his own mind to the mind of the others. Otherwise, it will only be by chance that their efforts combine to meet a single objective. For example, a man may imagine a ditch in the middle of a field that is exactly 12 meters long, 2 meters wide and 1 meter deep. How does he get others to help him create this ditch as he envisions it? If everyone speaks the same language, then he can describe the ditch. He might draw the ditch on a piece of paper with dimensions. He might use gesture, point to where the corners of the ditch should be and act out the process of digging. By whatever means possible, he must recreate the image of the ditch that he holds in his own mind within the minds of those with whom he wishes to cooperate.

The process of transferring thought from one mind to another is called communication.

Figure 1 The process of communication

We have the expression in English “he read my thoughts”, but we know that is impossible. We read about telepathy and mind reading in science fiction and books about the paranormal. Even if it is possible, it is certainly uncommon enough to make it impractical. Humans cannot share thought directly. The only thing that human minds share is the physical universe in which we live. In order to share thought, the human mind must alter the physical universe in some way that is perceptible by another human mind. This altering of the physical universe is the physical manifestation of the thought. The most direct means is to use the human body. We gesture and speak.

These physical manifestations need to be not only perceived but also interpreted. Many philosophers have lamented that our senses prevent us from knowing the physical universe perfectly. By their reasoning, it would seem that a thought could never be perfectly transferred from one mind to another since the receiving mind is using its senses. The transference is hindered even further due to the limitations on the sender’s part. It is difficult to manifest a thought perfectly in the physical. We often find ourselves struggling with the inadequacy of language. We use the English phrase “words escape me” or “words do not suffice”. We also have the English phrase “a picture is worth a thousand words,” but pictures also have limitations. Every engineer has struggled to show three-dimensional or multi-dimensional concepts on a two-dimensional piece of paper.

To communicate, we must manifest our thoughts in physical form, and the physical form that communication must take is called information.

Information can take on a transient or non-transient form. Voice and gesture are very transient. As soon as they occur they are gone. Primitive societies depend entirely upon such transient forms of information for communication. They rely on the oral tradition. Civilization advances when individuals communicate through non-transient forms of information, most notably writing. Writing is the detailed expression of thought using thin discrete lines in a physical medium such as grooves in stone or ink on paper. Writing enables far greater levels of cooperation over extended periods of time.

Gutenberg’s press can be thought of as an algorithm for duplicating information in an non-transient form. It empowered the Reformation and the Enlightenment. Maxwell’s equations unleashed an Information Age because they enabled man to manifest information in the electromagnetic spectrum. Now man can communicate through vacuums at the speed of light. Transient modes of information can be made non-transient by capturing and recording sound and light electro-magnetically. Combined with digital computers, information can be copied, disseminated and processed automatically (algorithmically). The objective, however, remains the same: transfer thought from one human mind to another.

A more common model of information is the Knowledge Hierarchy or Knowledge Pyramid model, popularized by Russell Ackoff.[1] In this model, information is comprised of data and knowledge is comprised of information. I find this model useless for a number of reasons. First, it treats information and knowledge as if it were a tangible thing that could exist without humans. As such, it is impossible to describe the model in anything other than the passive voice. Second, it promotes the idea that data can transform into knowledge or wisdom automatically without human involvement. If I have enough data, do I automatically get information, like trading in white poker chips for red ones? Third, it provides no explanation of success. Where do I invest to take advantage of the Knowledge Pyramid? The only result I have seen of applying this model is information overload on the soldiers.

Finite limits to communication

George Miller is sometimes attributed with creating the field of cognitive psychology with his paper, “The Magical Number Seven, Plus or Minus Two: Some Limits on Our Capacity for Processing Information.”[2] Miller presented the concept of a communication channel as having inputs and outputs. If we picture two partially overlapping circles, the right representing the input and the left representing the output, then the overlap of the two represents the transmitted information. Miller assessed the human as a communication channel.

“In the experiments on absolute judgment, the observer is considered to be a communication channel. Then the left circle would represent the amount of information in the stimuli, the right circle the amount of information in his responses, and the overlap the stimulus-response correlation as measured by the amount of transmitted information…. If the human observer is a reasonable kind of communication system, then when we increase the amount of input information the transmitted information will increase at first and will eventually level off at some asymptotic value. This asymptotic value we take to be the channel capacity of the observer.”[3]

Figure 2 Miller’s concept of the human as a communication channel

Miller presented the results of several studies on human ability to discern differences through their senses. In these studies, subjects were asked to discern stimuli such as sounds at different pitches, sounds at different volumes, solutions at different saliency, colors at different hues, colors at different brightness, shapes at different sizes, and so forth. Whether the sense was touch, taste, sight or sound, the results were remarkably the same. Miller found that, regardless of the input, the subjects could only discern on average seven unique inputs.[4] If the number of inputs went up beyond seven, errors dramatically increased. Miller found his asymptotic value, his channel capacity of humans. He noted, “There seems to be some limitation built into us either by learning or by the design of our nervous systems, a limit that keeps our channel capacities in this general range.”[5]

Thus it would seem that humans have a finite limit to communicate. Furthermore, nothing in the theory of the Turing machine or Maxwell’s equations addresses or alters the human channel capacity for information. The limits have always been the same, both before and after the advent of information technology.

I hope that the reader is not too terribly frustrated that nothing we have discussed so far has mentioned war. Nevertheless, we have laid the foundation for discussing information warfare. We are now equipped with some key definitions and theories. Let us quickly review.

• Information technology is based on Maxwell’s equations and Turing’s machine
• Turing’s machine executes any algorithm, but cannot create algorithms
• Humans create and understand algorithms
• Humans must communicate in order to cooperate
• Communication is the process of transferring thought from one mind to another
• Information is the physical form that communication must take
• Maxwell’s equations enable us to communicate in electromagnetic spectrum
• Humans have a finite limitation to their means to communicate
• Information technology in no way improves the cognitive limitations of man

Of all of these concepts, the most important to our discussion of information warfare is not any of those dealing with information technology. Rather, our discussion will center on the inherent human limitation to exploit information technology. The limitation has always been there. Thus, our discussion of information warfare does not begin with the advent of information technology but rather transcends the history of warfare.

Cooperation in warfare

In his study of combat units in the Second World War, S.L.A. Marshall observed

Green troops are more likely to flee the field than others only because they have not learned to think and act together. Individually, they may be brave and willing then as during any subsequent period, but individual bravery and willingness will not stand against organized shock.[1]

He made this deduction: “The emphasis should be kept eternally on the main point: His [the soldier’s] first duty is to join his force to others!”[2] An army may have only sticks for weapons and gruel for food, but without cooperation there is no army.

Miyamoto Musashi was a master Japanese swordsman, perhaps the master Japanese swordsman. In his work, The Book of Five Rings, Musashi instructs how a single swordsman can fight several opponents.

The idea is that even if opponents come at you from all four sides, you chase them into one place… Intent on herding opponents into a line… The thing is to win by sensing the opponents’ rhythms and knowing where they break down.[3]

Musashi recognized the inherent limitations of human cognition. He accommodated these limitations in his tactics. He changed the rules of the engagement to make the problem solvable. A human cannot take on seven attackers simultaneously, so Musashi engaged the attackers so that only one could attack him at a time. Musashi also exploited the limitations of human cooperation. A single combatant has no one with whom to cooperate. He can rapidly assess the changes in his environment and affect those changes necessary to achieve his objective state. The group of seven combatants must cooperate their efforts. They have the burden of communication. A highly trained opponent such as Master Musashi can change faster than individuals can communicate.

To use Colonel Boyd’s terminology, the single combatant can observe, orient, decide and act (OODA) without the burden of communication.[4] He can turn inside the others OODA-loop. It is a truth that transcends technology: place the enemy in a position that accommodates your limitations, including your cognitive limitations, and exposes your enemy’s limitations.

Roman legion

Since ancient times, armies have employed the concepts of overlapping fields of attention and hierarchal command of units as means of organizing. Both concepts are based on a fundamental limit in human cognition. The Roman legion used the concept of interlocking fields of attention well. The legionnaire carried a shield on his left arm and a short sword in his right. The short sword was used entirely for jabbing or thrusting, as opposed to slashing. They pushed with the shield and thrust with the sword. Each individual had a defensive left that overlapped with another individuals attacking right. The only person exposed was the person on the right most end of the century, or platoon.[5]

Figure 1 Overlapping fields of attention used by the Roman legion

The real superiority of the Roman legion was its extensions to interlocking fields of attention. The Greeks with their phalanx tactics had established such cooperation long before Rome, and yet the Greek phalanx melted before the Romans. The Roman formations had two distinct advantages to the Greek phalanx. First, the legionnaires had the ability to quickly rotate in their ranks, replacing individuals at the front rank one at a time as they were wounded or grew tired. The short sword accommodated this rotation where alternative weapons such as the pike could not. Second, the legions moved in modular formations rather than one single formation. The modularity enabled the Romans to alter their efforts to meet changes in the battle. It also compartmentalized the effects on the units. If one formation collapsed, it did not necessarily collapse all the formations.

The Romans were able to maintain a higher level of cooperation that accounted for the physical as well as the cognitive limitations of the soldiers. The results are astonishing. The Romans had no technological superiority on the battlefield, yet they achieved dominance in cooperating the efforts of the individual soldiers that the Greeks and Gauls could not match.[6]

Turning the flank

We so often attribute victory to turning the enemy’s flank that it seems cliché. Let us analyze from our perspective of cooperation what happens when a flank is turned. The enemy appears both on the front and on the flank. The individual at the corner is faced with a dilemma: either focus on the front or focus on the flank. His cognitive limitations prevent him from addressing both threats simultaneously. When the soldier on the corner turns, he is no longer protecting his neighbor’s flank. The neighbor now faces a dilemma and must turn or divert his attention. The effect cascades through the formation. Cooperation evaporates. Each soldier is left as an individual.

Figure 6 Flanking dissolves cooperation in a formation with cascading effect

Perhaps the enemy is not engaged to the front when the flank is attacked. Cooperation suffers nevertheless because now the soldiers must cooperate with other soldiers that they may not have trained with or in a way for which they were not prepared mentally. Figure 7 helps to illustrate this concept. Soldiers A, B and C along the front rank have trained together. When the enemy attacks the flank, either the whole formation must turn for soldiers A, B and C to cooperate as they are accustomed to, or soldiers A, M and V must turn as individuals and cooperate as strangers. The same effect applies to units.

Image:FlankGrid.gif

Figure 7 Flanking forces soldiers to cooperate with strangers

Du Picq observed that,

Four brave men who do not know each other will not dare to attack a lion. Four less brave, but knowing each other well, sure of their reliability and consequently of mutual aid, will attack resolutely. There is the science of the organization of armies in a nutshell.”[7]

One can observe the identical effects in modern battle. A line of fighting positions, or fox holes, will collapse when one fighting position falls. Flanking maneuvers work and have always worked because they destroy cooperation between individuals. We must ask ourselves, how does information technology change the execution of a flanking maneuver?

Man versus machine

It is the role of man to create. During the rise of the Industrial Revolution, millions of men were engaged in algorithmic tasks, that is, well defined, repeatable, replicable sets of motions. These tasks were part of mast production. Men were used in such tasks whenever and wherever it was cost prohibitive to use a machine. Such tasks usually involved the need for human vision and human dexterity. Since the beginning of the Industrial Revolution, it has been the role of the machine to displace men from algorithmic processes. Men displaced from such positions are free to enter more creative roles. The tale-tell example is the man is replaced by a robot only to be rehired as a robot repair man.

We have witnessed the same trend on the battlefield. Maurice of Orange created the 17th century practice of uniform battle drill.

Maurice differed from his predecessors in being far more systematic. He analyzed the rather complicated movements required to load and fire matchlock guns into a series of 42 separate, successive moves and gave each move a name and appropriate word of command. His soldiers could then be taught to make each move in unison, responding to a shouted word of command. Since all of the soldiers moved simultaneously and in rhythm, everyone was ready to fire at the same time. This made volleys easy and natural, creating a shock effect on enemy ranks. More important, soldiers loaded and fired their guns much faster and were less likely to omit any of the essential steps. The result was to make handguns more efficient than ever before, and Maurice increased their number in proportion to pikes accordingly.[8]

What we read in this short excerpt is amazing. All the battle drill we take for granted when reading history was initiated by one man. Maurice created the algorithm for matchlocks. It sounds simple on its face, but the repercussions were immense. He achieved a higher level of cooperation on the battlefield. In order to facilitate his new drill, Maurice was the first in Europe since ancient times to:

• Divide battalions into smaller units of companies and platoons
• Regularize marching in step to execute prescribed maneuvers
• Require uniform handguns
• Create a military academy for officers

What Maurice achieved on the battlefield at the turn of the 17th century is identical to what Henry Ford achieved in the factory at the turn of the 19th century.

Until the US Civil War of the 1860s, and in some unenlightened theaters later still, men were expected to serve as automatons, as mechanized portions of a great machine, just as Maurice had designed in the 1590s. The British Army achieved a greater lethality on the Napoleonic battlefield by achieving the highest level of cooperation, through pure algorithmic motion, from its highly disciplined infantry, the glorious thin red line. The British method was facilitated or perhaps even enabled by the superior manufacture of their musket, the Brown Bess.[9] After 1814, the lethality continued to increase, but not through specific improvements in drill and tactics, but rather through machines such as light breach loaded cannon, Shrapnel canisters and machine guns.

By 1914, the transformation was complete and Maurice’s innovation was forever obsolete. Captain Willy Martin Rohr invented modern squad level infantry tactics organize infantry in such a way that men could once again use their creativity to solve the problems about them. The embodiment of this approach the Germans called Strossstruppentaktik and Alftragstaktik. General Ludendorff recognized the advantage of the approach and spread it through out the German Army.[10] The approach is the foundation of the small unit tactics practiced in the US Army today.