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AI – Artificial Intelligence Demands Workers Stop Being Used!

Starting Premise. 1 Let us agree, for sake of a thought experiment, that a Human represents the ultimate Machine potential.  In other words, every Machine that a Human creates is a subset of Human capabilities.  Yes, a Machine may be stronger, faster, lighter, more durable, et cetera than a Human, however, the most capabilities with which a Human will be able to endow a Machine are those of the Human.

For the reader who wants to debate about Human flight, consider that the Human is capable of flight albeit extremely short survivable distances.

Back to the Future Past.  In 1867, American inventor Christopher Latham Sholes struggled with improving the performance of the typewriter.  If commonly used letter pairings such as S-T were struck too quickly, the mechanical linkages that transmitted the letter key selection to the striking of that letter on paper would get jammed.  The typist had to stop Work, turn attention away from source material, turn attention to the typewriter, untangling jammed keys, return attention to the typewriter keys, reset their fingers, check that the typewriter carriage was in the proper spot, turn their attention to the source material, and resume Work.

The speed of the typewriter (a Machine) was inhibited by the faster speed of the Worker.  Sholes’ solution to this problem was to separate the commonly used letter pairings and place the most frequently used keys on the left side of the layout.  This solution slowed the Worker so that the Machine could perform at its best.  Unfortunately, Human obsession with technology enables Machines to transform and evolve much faster than the Human being itself evolves.  Thus, the speed of the Machine today is inhibited by the slower speed of the Worker.

“Those who cannot remember the past are condemned to repeat it.” Reason in Common Sense – George Santayana, 1905.  In 2021, while computing Machines operate at speeds greater than that of Human thought, we must revisit System Solution design to avoid unintended consequences arising from lack of foresight.

“User” Anomaly.   Other than with respect to most electronic Machines (e.g., computers, tablets, smartphones, et cetera), the User role does not occur in Humanity (excepting for references to consumers of recreational drugs).   Drivers drive cars.  Passengers ride in cars, in buses, on boats, on planes. People wear clothes, sleep on mattresses, swing golf clubs, hit golf balls, swim in pools, ride bicycles, enjoy entertainment, et cetera.   Children play games, play sports, learn math, learn spelling, compose essays, read books, et cetera.

It is natural to discuss a homemaker using a stove, pots, and pans to make a meal and downright awkward to think of a User using a stove, pots, and pans…  “User”, while necessary at the outset of the computer industry, should have become passé not long after Donald A. Norman’s 1999 publication of The Invisible Computer.

Please take note:  When your child or grandchild asks for the iPad, they say: “May I play with/watch the iPad”.  They do not say may I Use it and (most important) they will grow to never Use computers in the future.  Just as when if everything were the color blue, there would be no color blue; when everything becomes a computer, there will be no more computers.  As goes the computer, so goes User.

In the context of Machines as subsets of the Human, it is fair to accept that most everything a Human may want to accomplish with a computing Machine was described by the Dr. Vannever Bush in his July 1945 Atlantic Monthly article As We May Think.  One can make the case that Humanity has only now, in the year 2021, recently delivered on the vision of Dr. Bush.  Further progress may be hampered by Humanity getting in its own way.

As We May Do. ‘Humanity getting in its own way’ is mistakenly accepting the User role as fundamental – that ‘User’ is doing something [as in the performance of Work = (Force x Distance) + (Thought x Time)] more than retrieving data from one Machine process and feeding it into another Machine process.

Computers are Machines. A Machine is an invention created by Humans to make work easier by multiplying the effect of Human effort.

When creating a system solution design comprising Machines that execute management science algorithms (e.g., Double-Entry Bookkeeping, Linear Programming, Off-Set Leadtime Planning, et cetera), placing the non-Value-Add User role at its center ensures the automation will never run faster than the slowest User role being fulfilled by a Human.

Unfortunately, as Humanity continues relentlessly advancing technology, what many Users today actually do is stare at refracted light (sometimes it is reflected as in the case of transmissive display technology) or listen to synthesized speech and populate data (through myriad input mechanisms) that cause a Machine process to take the next programmed step in emitting refracted light and/or synthesizing speech.2

What is fundamental is that which a Worker does, as in Work = (Force x Distance) + (Thought x Time). It is what a Worker does and not how they spend time that is fundamental and needs to be elevated in the revisiting.

System Solutions must be revisited knowing that the same Management Science and Physical Science has been automated both upstream, downstream, and throughout extended enterprise system solutions.

It comes as no surprise that the “Outputs” of one enterprise look a lot like the expected “Inputs” of another enterprise.  What becomes a surprise is when there is a tremendous mismatch between enterprise-to-enterprise systems especially in the post Y2K era.  Chances are good that an IT vendor and/or IT Employee convinced one or more Workers in one or both enterprise that they are so special that unique software must be written for them.

Back to the Future. Enabling Machines to automatically create Machine automation (i.e., computers programming computers) may require a breakthrough approach such as the movement from 3rd Person Design for 1st-Person Execution to the 2nd-Person Design + Execution.  This new design perspective may then enable the conceptualization of the “Mind” of the first Machine interacting within itself and its environment conceptualizing and realizing a “Mind” of a second Machine, and so on.

Time out & Back up.  Before attempting to wrap your head around the above paragraph, let us agree that, for Machine automation to achieve its potential, there would need to be a change; that something is broken and needs to be fixed.  The old saw says, ‘The first step in a cure is accepting that you are sick’.  So, what is wrong with what we are doing with computers today that precludes advancement, why is it that way, and what do we need to do differently?

Admitting Sickness.  Anecdotally, while information technology has advanced exponentially, the increase in marginal productivity from the investment in information technology has been in decline.  In other words, the same or more investment of Time + Talent + Treasure into exponentially advancing information technology is met with smaller and smaller improvements in outcome.

In 2021, every Design Engineer has multiple Computers (e.g., design workstation, notebook computer, tablet, smartphone, et al) at their disposal each of which are over 1,000,000 times the power of the single computer they had in 2001.  New product development success has not advanced at the rate of the empowering underlying Machine automation.

With an overabundance of computers, most product development continues progressing incrementally with the success of new product development initiatives being not that much greater than the success of a Startup.  It is no surprise that bright, energetic, talented engineers abandon what truly are exciting projects in large enterprise projects, throw caution to the wind, and become entrepreneurs.

Let us assume this flagging growth in productivity in the face of exponentially growing technology resource is true and that it is a problem. What is the Root Cause of this paradox?  Simply stated, the Root Cause of today’s declining marginal returns in productivity and operational efficiency from investment in Information System Solutions is failure of Computer Science to implement Information Science for Optimization of how we Live – Work – Play.  This failure will be overcome by establishing and working from a new perspective.

1970s-1980s.

The rise of User. Fifty years is not a very long time in the history of Humanity.  In the early 1970s, long before any talk of computer User Experience or Human-Machine Interface (HMI) most all HMI was punched cards and paper tape data input resulting in delivery of fan-folded green bar printed paper information output.

Green bar report production, sorting, delivery, storage, and archiving became an around-the-clock operation within each company that implemented computer automation earning itself a newly established functional department named Data Processing or DP for short.

DP initially served business functions directly responsible for: keeping track of money (Accounting), spending money on Workers (Payroll), and spending money on things (Materials).

Accounting, Payroll, and Materials Workers became the primary consumers of the output.  While these Workers certainly used the DP department output, their primary role remained Accounting, Payroll, and Materials. Each of these Workers was not a computer user or User for brevity.

Humans continued advancing computing Machines enabling the concept of online transaction processing (OLTP) or being “online” with the computer.  Through typewriter-style keyboards, stylus, light pen, microphone, camera, mouse, joystick, et cetera humans fed data input to the Machines.  Through video display terminals, speakers, printers, and plotters humans consumed the information output from the Machines. Data Processing or DP evolved to become Management Information Systems or MIS.

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Stewart A. Skomra
Stewart A. Skomrahttps://omniquest.world/
Stewart A. Skomra is CEO of OmniQuest™, the leading developer and supplier of software to assist engineers in achieving optimized product designs in the automotive and heavy equipment industries. For over 35 years Stewart has driven New Product and New Market Development Computer-Aided Design & Computer-Aided Manufacturing, Machine-to-Machine/IoT – Internet-of-Things, Supply-Chain Management, Auto-ID, and Wireless Technologies. From Blue-Chips including IBM, Intel, Qualcomm, and Trimble Navigation through multiple startups, he has led development initiatives serving industries including manufacturing, construction, distribution, transportation & logistics, wholesale & retail, consumer packaged goods, along with finance, insurance, healthcare, and multiple energy fields.

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