Catch++
Software
Overspecialization
and the
Metaphoric Programming Agenda
Joseph Thames
FOREWORD By Lee Carroll ............................................................. xiii
PREFACE............................................................................................... xv
PART I INTO THE HOLOGRAM ...................................................... 1
Chapter 1. Anomie and Renaissance....................................... 3
Computers and Applied Science .................................................... 3
A Hidden Crisis Within the Myths ............................................ 7
Diminishing Returns Since 1965............................................... 7
Unshifted Paradigm................................................................... 9
The Computer Technocracy ........................................................ 11
Non-Equilibrium in the Division of Labor ................................ 14
The Hacker’s Compulsion ...................................................... 16
Labor Sovereignty .................................................................. 17
The Numerical Exodus of Computer Science .............................. 19
Symbol Crunching - The Compiler’s Legacy.......................... 20
The Symbolic Mirage ............................................................. 21
Artificial Intelligence - A New Lease ....................................... 22
The Emperor’s New Intelligence.............................................. 26
Synthetic Mathematics, A New Perspective.................................. 27
The Analogy of Music.............................................................. 27
Reductio Ad Absurdum........................................................... 28
Synthetic Logic........................................................................ 28
Inductive Reckoning................................................................ 29
The Superficial Science .......................................................... 30
The Legacy of Labor Sovereignty ................................................ 31
The Economic Growth Mechanism ........................................ 31
The Co-dependence Constraint ............................................ 32
The Lost Kaizen Alternative..................................................... 33
A Proletarian Monopoly........................................................... 33
The New World Order................................................................... 34
Transmutation of Creativity..................................................... 34
Koestler’s Reformation............................................................ 36
The New World Orchestra....................................................... 38
The Nonlinear Optimization Imperative................................... 38
Chapter 2. Visions Of Need - 1965 ......................................... 41
1965 Retrospective........................................................................ 42
The Cost-Push Dilemma......................................................... 42
Promising Avenues for Computer Research ......................... 43
Impedance to Engineering Demand ....................................... 50
The Calculus Programming Misconception ........................... 55
Visions Fulfilled 1975 - TSPROSE ......................................... 57
The Professional Software Approach to Engineering.............. 58
The Driver-Mechanic Scenario ............................................. 60
Calculus Misconception Revisited.......................................... 61
The Crux of Scientific Programming Difficulty........................ 63
Diminishing Returns and Stagnation............................................. 68
Missing Addiction Linkages............................................................ 69
PART II THE POWER OF BABEL ................................................. 71
Chapter 3. Market Control and Stagnation........................... 73
The Third Generation War ............................................................ 74
Encirclement Plan .................................................................. 74
The Recapture Dilemma
....................................................... 75
Fighting Machines ................................................................. 76
Blown Engineering Bridges ..................................................... 78
The Language Throttle .................................................................. 81
The Missing Link to Demand-Pull........................................... 81
The First Great Syntax Quake................................................ 83
Homogenization and Centralization ........................................ 85
Lingua Algorithmica – A Paradigm of Technique.................... 86
The Hidden Program of Control ................................................... 89
An Image of Permanence ...................................................... 90
Number Crunching Deferred .................................................. 92
Marching Software Attrition ..................................................... 93
The Monopolist Imperatives .......................................................... 93
Control of Innovation ............................................................... 94
Control of Customers ............................................................. 98
Imbalance Momentum .......................................................... 99
The Dark Age of Scientific Computing........................................ 100
Chapter 4. The Programming Army ...................................... 103
Centralization and Entrenchment .............................................. 104
The Lure of Recycling .......................................................... 104
The Unbundled Market ......................................................... 105
The Waterfall......................................................................... 106
The Modeling Imperative....................................................... 107
A Perverted Division of Labor...................................................... 110
The Perfect Specification...................................................... 111
Volatile Engineering and Higher Math................................... 112
Persistence of Algebraic Manipulation.................................. 113
Dynamic Differentiation and Synthetic Calculus................... 114
Paradigm Lost ...................................................................... 115
The Labor of Calculus Articulation........................................ 116
Of Mercenaries and Priests......................................................... 118
Formality, An Escape from Problem Uncertainty................. 119
The Training Pool................................................................... 119
The Attraction of Staple Recycling........................................ 120
Classified Program Flow........................................................ 122
Narcissus and Narcosis........................................................ 123
Efficiency at All Costs........................................................... 125
A Love of Obscurity............................................................... 125
The Hacker Imperatives............................................................... 127
The Hacker Generation......................................................... 128
A Fashion Agenda................................................................. 129
Hollywood Programming....................................................... 130
A Divine Wind.............................................................................. 131
Another Kind of Anomie......................................................... 131
Eric Hoffer’s Prescription....................................................... 134
The Power of Creative Addiction........................................... 136
A Community of Bazaar Innovations.................................... 137
Foundations of Renaissance....................................................... 139
PART III CRISIS AND RENAISSANCE...................................... 141
Chapter 5. The R & D Crisis..................................................... 143
The Demand-Pull Cycle.............................................................. 143
Staple Recycling.................................................................... 146
Staple Saturation................................................................... 147
The Web Anomaly................................................................. 149
The Commoditization of IT.................................................... 150
Empires and Fortresses.............................................................. 151
Abandoned Science.............................................................. 152
James Martin’s Fortified Wall................................................ 153
Inverse Productivity............................................................... 155
The Programming Barrier—Paving the Waterfall....................... 156
Tempting Foreign Armies...................................................... 157
Demand-Pull Counterweights................................................ 157
Demand-Pull Initiatives................................................................ 158
A Chip Maker’s Solution........................................................ 160
Matrix Arithmetic for Everyone............................................. 162
The Productivity Paradox............................................................. 162
Economic Measurements..................................................... 163
Industry Debate - Utility vs. Power........................................ 165
Atrophy of R&D Computerization.......................................... 167
Summary of the Evidence..................................................... 170
Economic Dynamics of the Computer Market............................ 172
The Unfinished Automaton.................................................... 172
Media in Equilibrium.............................................................. 173
Growth Cycles—Short and Long Term................................. 174
The Burden of Application Diversity...................................... 175
The R & D Market................................................................. 175
Artificial Growth via Media Turnover..................................... 176
Economic Imbalance............................................................. 177
Open Source Anomie............................................................ 178
Labor Sovereign Vision......................................................... 179
Artificial Aging and State-of-the Art Lag................................ 183
Chapter 6. The Meta Science Agenda.................................. 185
Engineering Imperatives.............................................................. 185
Impedance to Engineering Adaptation.................................. 186
Engineering Demand and Mathematical Supply................... 187
Very Rapid Prototyping......................................................... 189
Metaphoric Modeling.................................................................... 193
Holistic Posing vs. Reductionistic Solving............................ 194
Calculus Reform.................................................................... 195
The Bourbaki Paradox........................................................... 198
The Anatomy of Scientific Computing......................................... 199
The Prediction Domain.......................................................... 199
The Control Domain.............................................................. 202
Calculus Arithmetic Infrastructure......................................... 205
The Meta Science Paradigm....................................................... 206
Meta Calculus........................................................................ 206
Optimization Re-Engineering................................................. 209
Hierarchic Meta Calculus...................................................... 215
The Meta-Science Manifesto....................................................... 224
ORE Mining and Recasting................................................... 224
Parallel Meta Calculus........................................................... 226
Higher Meta Science............................................................. 228
Meta Engineering................................................................... 228
AI in Auto Synthesis and Auto-Modeling Research.............. 230
Auto Synthesis and Optimization Broadcasting.................... 232
Concurrent Engineering Optimization................................... 234
The Meta-Science Era................................................................. 236
The New Fulcrum.................................................................. 236
The 21st Century Paradigm Shift.......................................... 237
Chapter 7. A Renaissance Business Model......................... 239
Consultative Marketing................................................................. 240
Mentoring—The Problem-Solving Partnership..................... 240
A Service With Economy of Scale........................................ 245
Prospecting for ORE and Vertimaps.................................... 246
Shifting the Burden of Diversity............................................. 246
Meta-Science Consultants – Morphing Academia 101........ 248
Global Consultative Matrix – Morphing Academia 102........ 248
Morphing the Division of Labor.................................................... 249
ORE Mining Metamorphosis................................................. 250
Meta Engineering Proliferation.............................................. 253
Meta-Meta-Science – Vertical Application Wizards............. 253
Experential Science............................................................... 254
Super Productivity – Fueling the R&D Race............................... 255
CAD Diffusion........................................................................ 256
Invention CAD and Patent Surrogate Protection.................. 258
The New AIM – Auto Intelligence Modeling........................... 259
The Post-Industrial Re-Evolution................................................. 260
Seamless Integration Groupware.......................................... 260
CEO-CAD-CAM-CEC Production Platforms....................... 261
Metamorphosis of the Computer Industry............................ 262
Building a Global Collaborative Community................................ 263
The Eloi-Morlock Continuum................................................. 263
Networking Partners for Profit............................................... 265
Reward Systems and Revenue Incentives........................... 267
Agency Program Offices and Venture Holons..................... 267
Barter Currency and Grass Roots Economic Power........... 268
Alliance Infrastructure ........................................................... 269
Business Opportunity Marketing........................................... 271
Engineering the Renaissance..................................................... 273
Appendix: Meta Calculus Example Programs..................... 275
Meta Calculus Holonic Architecture............................................. 276
Basic Holonic Templates............................................................. 277
Chemical Equilibrium – Nonlinear Equations........................ 278
Admittance Circuit Fitting – Scientific Method...................... 279
Nested Holonic Templates.......................................................... 282
Pilot Ejection Safe Altitude-Speed Profiling........................... 282
Bipropellant Rocket – Implicit Differential Equations............ 288
Three-Stage Rocket Design Optimization............................ 289
Chemical Kinetics – Scientific Method.................................. 292
Optimal Design and Control (ODC)...................................... 298
Expanded ODC Template – Wing Design Optimization....... 299
System Engineering End-User Perspective................................ 303
FOREWORD
By
Lee Carroll
Steve
could hardly sleep. When he thought of the project at hand, his heart beat
faster! This was heady stuff ... if he was successful, it could change the way
everyday people did things ... perhaps turn an industry around! The contribution
of the Company with this new idea might even bring positive change to the
planet! He couldn't wait until he got to the office. His team was the first to
tackle the new design... and he knew he could do it.
Later
the next day, after hours at the computer keyboard, Steve felt defeated... like
he had been beat up. The order for the new design sat in front of him. Earlier
that day he had even received a phone call, letting him know that stage-two
funding was a shoe-in .... everyone upstairs was excited... and the
"suits" had even come over to his department to congratulate him! ...
and yet he still stared at the screen in disbelief. Steve didn't have a computer aided design program that even came
close to addressing his math problems.
He hadn't really given it a thought.
He assumed these kind of tools were "out there," and that you
simply needed to obtain the correct vendor.
But no one had anything at all for him ... since the structure of his
problem was unique.... of course it was... it was a new concept!
Steve
realized that he would have to write the code himself... a task almost as
daunting as doing all the research by hand... since in order to write the code
to address the problem, he had to almost do the work anyway! To make matters worse, he had forgotten much
about programming since he had done it last. He would have to increase the
budget to allow for at least two more programmers and a couple of
mathematicians, and triple the estimate of time it would take to reach the
target. With a black feeling in his stomach, Steve reached for the phone to
make the necessary call.... letting management know that their
"prize" project had just gone into the dumper.....
Fantasy,
or fact? What do our leading edge researchers face today when they approach
R&D that doesn't conform to CAD programs, relational databases, spreadsheet
approaches, or existing math models? Could it be true that this new high-tech
computer generation has a giant black hole... right where it should be the
brightest? If so, how did this happen... and is there a solution at hand?
PREFACE
Why has the computer industry been imploding in recent years? What happened to the enormous growth in productivity portended by the Internet? Why hasn’t our space program leaped ahead from the incredible reduction of computer costs? Is there some fundamental catch that is holding back progress?
To understand what is happening in the computer industry, the flagship of our age, it is not sufficient to look at the recent events of the desktop computer era. Today’s conditions are the result of 50 years of evolution, following a trajectory predetermined by industrial-age assumptions about the division of labor. In our post-industrial age, these assumptions have led to economic stagnation. Computers have the potential to lift us from the cultural shackles of the industrial age, but industrial culture is what we have known for 200 years, and we have shackled our computers with ingrained assumptions about industrial specialization that we must literally back away from if we are to achieve the true promise of the post-industrial information age.
The early computer decision makers, being industrial thinkers, regarded computers as production factories. They organized computer processing in the factory image, transferring computation technicians from the dispersed work cells of R&D application departments to centralized computer departments, where they were trained as a guild of middlemen in the new art of programming. These new laborers would thereafter become the primary performers and directors of computer work. But without the vital apprenticeship knowledge of application needs that they left behind in the diversified scientific laboratories and engineering offices, they became incomplete units of unified skill without purpose other than the specialization of logic technique—a kind of mental myopia that has now come back to roost after 50 years. This mental focus has given rise to what is now the crucial dilemma of overspecialization—what I am calling “Catch++”.
Creation of this middleman guild was a pivotal move which shaped the new computer culture, because its members no longer looked outward to model and adapt modes of computer communication natural to the worldview of computer users. The mental focus tended to isolate them from this worldview. Instead, they adopted the algorithmic or logic perspective of computer processing as the guild’s turf lingo. Even after the guild-army later dispersed from its centralized computer camps, and evolved into a culture, it continued to guard and defend this turf, by endlessly articulating and specializing the lingo, so that only specialized training was adequate to its use, and the dedication this required discouraged amateurs from “doing it themselves.” As it turned out, this was a pivotal turning away from economic productivity. It guaranteed that future programming technology would become ever more labor intensive rather than computer intensive, even though labor cost would continue to rise and computer cost would dramatically fall. This divergence from economic leverage in software development is the cause of the persistent IT productivity paradox, noted by leading economists, and a major source of stagnation in the world economy.
This guild monopolizing trend in the evolution of the computer division of labor is an industrial side effect that was already well understood by those who studied the industrial revolution. The regimentation of labor based on uniformity of skill was called mechanistic by the great French sociologist, Emile Durkheim, in his major work, The Division of Labor in Society (1893). He regarded regimented functional organization as a primitive societal form, and contrasted it with the more evolved cellular division of labor based on complementary differences, like marriages, from which we derive the concept of synergy. He called this more evolved labor division organic.
The mechanistic army of uniform sameness and the cellular units of organic differentiation were polar opposites of organization that would shape the evolution of progress in profoundly different ways due to extreme differences in sensitivity to societal needs. As the factory-mass model pervaded our consciousness from the legacies of Ely Whitney and Henry Ford, we created a bureaucratic culture in the image of our machines, from our classrooms of mass education to our massive government bureaucracies. Industrial specialization became unquestioned and pervasive, even in our medical professions—supposed to epitomize sensitivity. If insensitivity to differential need and to the need for differential empowerment of individuals were observed side effects, they were considered small prices to pay for the manifold leverage of industrification.
Durkheim observed that these two opposite forms could not coexist, and that once the mechanistic guild had gained the upper hand, it would act to eradicate the organic cells in subtle ways in order to preserve itself. This exclusion propensity led to a non-equilibrium condition Durkheim referred to as Anomie. Anomie is a condition of mismatch of capabilities to needs that evolves to a stalemate condition, somewhat like a “Catch 22”. Hence the use of the term “Catch++” deriving from C++, the modern programming language that epitomizes the intense overspecialization of computer lingo.
The anomaly I am calling “Catch++” has several aspects, one of which is the monopolistic exclusion propensity itself, which because it is based on job survival, is stronger than economic imperatives. It is survival-driven obsolescence. This is the reason economically obsolete disciplines persist—the “John Henry”[1] inertia factor. Another aspect is the isolation from the direct experience of end-user needs and their economic imperatives—a lack of external vision of what applications are needed, what innovations enable them, and how these innovations develop economic leverage. This is the missing mother of invention effect. It tended, by default, to turn the evolutionary path in the wrong direction—toward the inverse leverage of anomie. Intermediate needs of the middleman themselves became the default step-mother of invention, leading to overspecialization and fractionation[2], which reinforced the exclusion and the dependence of the end-user upon the middleman role.
But overspecialization weakened the specialist also. Isolation from external needs created a co-dependence upon the outer knowledge of end-users, except within the staple nexus of common knowledge, which became the default focus of least difficulty—standard functions understood by all. As the end user was subtly excluded from the means of doing the programming work by its overspecialized complexity, non-staple (custom) application development became a tortured information exchange and negotiation between the chosen representatives of the two factions (programmers and end-users)—the development of formal specifications. Because the workflow charts of this process resembled a series of cascades, it was called the waterfall method. It was a method that pleased nobody, but was an early protocol for the achievement of precision of meaning, necessary for the encoding of algorithms—computer thought. Where it failed most miserably was where the requirements being specified were unknowable without the experimental evolution of prototyping. As it turned out this occurred in all but the well established (staple) business functions that had already stabilized in their societal evolution.
The inadequacy of the waterfall approach to software specification has motivated a plethora of approaches over the decades, attempting to improve the communication of requirements to the programming guild. But in all of this effort, the industry lost sight of the fact that algorithmic programming became obsolete almost as soon as it became the dominant method of programming. Its basic notion quickly became counter-productive as computers became cheaper than manpower. Algorithmic programming became a formal direction of the computer industry after 1960, and computers became cheaper than manpower in about 1965. The basic notion of algorithmic programming can be stated as: applying manual labor to adapt human thought to computer thought. Thus it is the path to greater labor intensity.
The formal specification of algorithmic programming
adopted in 1960, was an international standard language known as Algol.
In some ways it was a reaction to the introduction, in 1957, of a fundamentally
different notion of programming, which can be thought of as metaphoric
programming. The basic notion of metaphoric programming can be stated as: applying
computer leverage to the adaptation of computer thought to human thought. Algorithms
are generated by computer processing of metaphors which simplify the expression
of programs. Thus it is the path which trades cheap computer time for
expensive labor—what computers were invented for in the first place.
Fortran was the first metaphoric language. It created a metaphor that applied the symbology of algebra, a highly familiar form, to describe a chain of computer arithmetic. It was not algebra at all. It merely used algebraic symbology to simplify the human expression of programs, thereby enabling computer amateurs (engineers and scientists) to do their own application programming. This was the real solution to the waterfall—eliminating the middleman. It was the first challenge to the authority of the programming guild and its costly method of algorithmic programming.
Metaphoric programming was especially cost effective in scientific computing because scientists and engineers were not daunted by programming. They found it easier than explaining their problems to programmers in the forum of the waterfall. Since scientific programs were not usually designed from a set of requirements as common in guild practice, but rather evolved from incomplete ideas as a series of prototypes in a learning process, the cost of the middleman waterfall approach became intolerable, as it tended to increase exponentially as middleman labor was iterated in the adaptive prototyping process. Freed from the cost and constraints of the waterfall, scientists and engineers started a revolution in metaphoric programming. The demand created for new scientific computers rendered its originator, IBM, into the first monopoly of the computer era.
Unfortunately, the leverage of metaphoric programming was unexpected by IBM businessmen, and later appeared dangerous to IBM’s lease market dominion when it was exploited by a deep-pockets competitor, General Electric. GE introduced an even simpler metaphoric language, Basic, designed to stimulate end-user programming along with the new computer marketing method, time-sharing, which had not been a part of IBM’s original product mix. IBM reacted to GE’s threat by conducting an all-out competitive vaporwar—not only against GE, but also against the leaders in the scientific computing arena, Control Data Corporation and Xerox Data Systems, using the vaporware strategy (both hardware and software) later exploited by Microsoft. This was no small engagement, but was rather a total assault on the scientific market that had built the computer industry. The vaporware “fighting machines” were bait-and-switch customer diversions that were discontinued and written off after they had successfully diverted customers from the competitor machines, leaving the committed customers only the standard mainframes IBM had originally intended them to acquire.
This vaporwar proved highly successful in driving GE from the computer business. But it went much further. It was an implicit message that anyone who pursued a metaphoric programming agenda, might encounter IBM’s wrath again. And what CEO would dare such a move, after IBM had driven mighty GE from the computer marketplace. Thus began the great retreat of the R&D computing market, which had been steadily advancing metaphoric simulation programming by end-users, and was positioned for a quantum-leap of metaphoric programming to a new regime of optimization computing, as the result of a breakthrough in calculus arithmetic[3].
Why did IBM, who had led the metaphoric revolution, adopt such a countermove? Quite simply because in an industrial lease market, counter productivity is profitable. Algorithmic programming took longer to develop software; therefore it prolonged lease life. Metaphoric programming not only shortened software development, it was less computer dependent, making it easier for competing manufacturers to carve out important market niches. This had quickly happened in scientific computing, and threatened IBM’s overall dominion primarily from that quarter. IBM removed that threat, for the next couple of generations, via its third-generation vaporwar.
In this turnabout, IBM threw all of its weight behind algorithmic programming with its own version of Algol, called PL/I, at the precise historical moment when algorithmic programming passed its point of diminishing returns[4]. But at the same time, IBM endowed the programming culture with a new mandate and a new agenda that would shift the programming resources of the world for a generation, and become the route to the guild’s unassailable dominion over the industry, even after IBM’s dominant market power was eclipsed by Microsoft and Intel. The new mandate was software recycling, a make-work agenda that primarily served IBM and the guild at the expense of economic progress. No longer need the guild army concern itself with the waterfall, since old software was a perfect specification for new software. Nor was prototyping—which made algorithmic programming prohibitively expensive in R&D—necessary to produce correctly functioning recycled software. Driven by the unavoidable cycles of hardware change, accelerated by the secret strategy of microprogramming which made hardware portable under a stable blanket of software, nobody had any choice but to go along with the new agenda, which swelled the ranks of the programming culture.
A major boost to the guild campaigns were the new graphics devices which began the shift to developing cosmetic faces for the old recycled software. Over the next four decades this became the major source of employment for the expanded programming guild—the focus on graphical user-interface programming.
Recycling of software into IBM’s PL/I language gave IBM leverage on its competitors that was not tolerated for long. AT&T, another powerful monopoly concerned about hardware independence of software, developed a machine-independent algorithmic language C, and used it to develop a portable operating system, Unix. This would widen the commitment to algorithmic programming to all computers, large and small. C became the universal lingua franca of software recycling, often being used to convert PL/I software. A closer match to the hardware than any other algorithmic language, it also became a universal surrogate for machine (assembly) language. Hardware device drivers for new hardware were almost universally written in C. This low-level focus required a mind-warp (pointers) from the outward worldview of users to the inward-focused expression of machine-oriented logic, thus taking the consciousness of a generation of programmers further into the algorithmic technique of the hardware. Needless to say, this also repelled amateur programmers, intent on doing their own application programming.
Thus low-level algorithmic programming became more and more entrenched in the computer industry in the 1970s. Soon this would explode in a frenzy of recycling as the semiconductor industries paved the way for a consumer market for computers. Then came the “big bang” of the personal computer, a vehicle for industrial commoditization of software staples that could be recycled from the large computers and cosmetically dressed in all sorts of graphical styles, to create a fashion agenda for market turnover. Enter software mass production and the rise of Microsoft and Intel, the inheritors of IBM’s monopoly, to capture the explosive consumer computer market pioneered by Apple.
Microsoft, Intel, and IBM, have always been consummate manufacturing and marketing companies. They have capitalized on standard products, which they developed and leveraged with aggressive business prowess that would make John D. Rockefeller and Henry Ford proud. They are true extensions of the industrial age of staple commodities which coerces its market into the mold of its product mix, in order to exploit extreme economies of scale leverage. This posture motivates monopoly domination because consumers would the coercion and select alternative products, if available at affordable prices. Historically, natural monopolies have always adopted this posture of limiting consumer choice. Of the three, only IBM, being primarily shaped in an era of lesser scale economy, where service was a crucial part of its product mix, has historically developed a strong service orientation as an essential part of its sales force. Microsoft and Intel emphasized the mass-production focus of classic commodity manufacturers.
Extreme economy-of-scale leverage is an essential requirement to compensate for extreme production costs. Only staple commodities, the products that the whole market requires, have this immense leverage of scale. With the explosion of scale provided by the advent of personal computers, the software middlemen were given another generation to overspecialize software lingo without market restraints to control labor costs. Thus shielded from economic imperatives, algorithmic specialization became an unquestioned order of evolution in the division of labor, adopting the familiar industrial assumption that has gone unquestioned for 200 years.
Once again, metaphoric innovation offered the opportunity to break free of the algorithmic myopia that had gripped the programming guild. Object-oriented programming, a means of developing re-usable component software appeared in the metaphoric simulation language, Simula, and was adopted as the wave of the future—not for its original metaphoric purpose of simplification, but for greater algorithmic sophistication. This high-level innovation was grafted onto the reigning standard algorithmic language, C, creating C++, a plunge into esoterica so intricately articulated that many years of practice are required to master it.
C++ is but the epitome of overspecialization. It later spawned Java by Sun Microsystems, and C# by Microsoft, in a continued trajectory of economic anomie. Burdened by the focus on cosmetic articulation of graphical user interfaces and graphics rendering for computer games and movies, the whole industry has become focused on the high-cost beautification of staple (common) images—the default path of least resistance, requiring only superficial application knowledge, but a great deal of expertise in algorithmic technique.
The situation of anomie in computer software today is the result of the middleman guild culture having been over-expanded and overspecialized for more than two generations, during which production was sustained by artificially recycled demand through cosmetic rendering of user-interface styles afforded by computer hardware advances. The recycling of broadly understood staple commodity software (operating systems, word processors, accounting systems, drafting-CAD programs, etc.) for each new generation of hardware and display devices became the primary business of IT, while programming became more and more labor intensive due to overspecialization. As programming languages became increasingly technician oriented and esoteric, the ranks of programming technicians swelled to populate the build-out of all of the staple-commodity niches in the world economy. The computer industry became an analog of the fashion industry, as relatively modest increases in function were made different and new by stylistic changes in user interfaces, in a relatively small number of staple commodity tools—essentially the products we associate with Microsoft.
To most industry outsiders and the majority of insiders, the only evidence of the anomie is a productivity paradox that has perplexed economists, industry leaders, and the public for decades. On the one hand we have incredibly cheap and powerful computers, but on the other we can only afford to use them for standard tasks, because the development of software for custom tasks is incredibly expensive, and continually becomes more so. Meanwhile, our computer-based R&D which requires custom prototyping of new software, has deteriorated from the enormous burden of software development cost. The marginality of our space program is an example of the impact of this deteriorization.
Now this agenda has all but exhausted itself, and the programming guild has become too overspecialized and economically exposed to foreign competition to maintain its own sustenance. Industry evolution has produced a staple cul-de-sac of overspecialization—a dead end that must be backed out of in order to move forward again. This drawing back to leap is well known in biological evolution, and appears to have been important in the development of the human species on Earth. Arthur Koestler referred to it using the French phrase, recular pour mieux sauter. It is a de-differentiation to a less specialized state followed by a major shift in the direction of evolution toward a growth path which escapes the economic stagnation of the cul-de-sac.
The nature of this staple cul-de-sac is what I am calling a “Catch++”, with obvious analogy to the bureaucratic anomaly characterized in the famous phrase from Joseph Heller’s World War II novel, “Catch-22”. It is a peculiar eco-sociological stalemate between two co-dependent “species”, programmers and end users, that is the result of the way the computer-industrial “game” was originally organized and later manipulated by powerful Darwinian conflict.
Durkheim had predicted what happens when mechanistic labor armies, out of touch with societal needs and bereft of vision as to what to produce, get the upper hand over diversified organic labor which is directly in touch with and guided by needs. The economy feeds on itself, b