Intelligent Work

Intelligent work,[i] as opposed to work accomplished by natural causes, is work performed in an intelligent fashion and therefore requires machines with embedded intelligence[ii].  The use of terminology regarding intelligence with respect to science causes much misunderstanding and confusion because the relationship is different for the materialist vs. ID viewpoints.

The definition of science varies widely.  Merriam-Webster’s first definition is “the state of knowing.”  This definition applies to anything that is considered knowledge, which implies that something that is not known is not science.  There are many aspects of physics that are not understood (e.g., entanglement, dark matter, and energy), and by Webster’s definition would therefore not be science.  For the purposes of this paper, science is defined as “the systematic knowledge the natural physical world gained through observation and experiment.”  “Natural physical world” means without intelligence involved.  If this definition was universally accepted, a lot of confusion and problems would be eliminated, author’s opinion.

Intelligence is defined as the ability to gain and apply knowledge.  Intelligence is in the realm of philosophy and has a hierarchy of levels: information, logic, and abstract.  An analogous hierarchy in the realm of science regarding space/time is: distance, speed, and acceleration.  Most people think of intelligence in terms of a combination of the logic and abstract forms.  Engineers use all three levels; abstract intelligence for design, logic for processing, and information for specifications, design documentation, data etc.

Intelligence, at all levels, has no meaning in science in the sense that in the natural world, there is no measuring of states, there is only the direct interaction of matter and energy according to the laws of physics.  Measuring and processing state variable information is intelligent activity and only occurs in matter/energy that has been manipulated by intelligent work to embed intelligence.

The fact that logic processing and abstract thinking are the results of “activity” or work and not a static thing like information is the center of the arguments presented in this paper.  It will be demonstrated that intelligent work requires matter/energy with embedded logical or abstract intelligence, which results from intelligent processes executed by machines that can only be created by an abstract intelligent machine.  It will also be demonstrated that all machines are beyond the reach of natural causes.

Strictly speaking, engineering and biology are not totally science by these definitions because both fields involve embedded intelligence.  Natural causes have no analog to logic and no mechanism to perform logical functionality.

Intelligent work differs from naturally caused work because intelligent work can:

1. perform the work on demand determined by specified state variables and/or logical signal(s), e.g., the temperature is a specified value, a mouse is present, the crankshaft is at a specified angle, the switch is “ON”, or some computed algorithm is a specified result, and
2. control the use of energy, i.e., the form, time and profile, location, direction and amount are all specified[iii].

The “on-demand” requirement is a logical operation that requires an output which has at least two states based upon the states of the input(s). Natural causes cannot perform intelligent work for two reasons:

1. The only inputs available are the state variables resulting from a previous naturally caused event with no intelligence involved, and
2. The only output is the unitary most stable equilibrium of the system.[iv]

In other words, natural causes have no mechanism for logical functionality.

What is an Intelligent Process?

An intelligent process,[v] defined to exclude natural processes, is a series of actions designed to achieve the desired result.  All intelligent work is part of an intelligent process.   The “actions” are performed by machines.  Machines use intelligent processes because they must provide a specified end based on logical decisions.  Intelligent processes can be thought of as a hierarchy of actions, layered, both vertically and horizontally such that when executed, the actions achieve the desired goal. 

Characteristics of an Intelligent Process

An Intelligent Process is Action; It Requires Machinery and Energy to Function

An intelligent process is not a static thing, it involves intelligent work, which requires functioning machinery, designed to accomplish a specific goal.  When an intelligent process is running, it is continually consuming energy due to the on-going actions required to implement the embedded intelligence.[vi]  This contrasts with a natural process which is consuming energy only during the time the natural state change is taking place.

An Intelligent Process Requires Specified Initial Conditions

Each step of an intelligent process requires specified initial conditions.  The first condition is the specified arrangement of the matter/energy involved (design) in the intelligent process coupled with setting all state variables, e.g., load software, charge batteries, set switches to specified positions, fill fluids, etc.  The action of an intelligent process step will normally change this arrangement and will be the initial conditions of the next step.  Stated differently, intelligent processes are creating a specified result, requiring specified initial conditions being acted upon by intelligently guided energy.  Natural processes will lead to an unspecified result that is determined by previous natural actions reacting to the available free energy.  Both, intelligent and natural processes follow the laws of physics.

Intelligent Processes Must Be Started by Intelligent Action

Think of any intelligent process – it always starts with some event or intelligent decision to take the “first step”.  All processes require the use of controlled energy, so “start” is often the action of activating the power source.

Intelligent Process Steps Require Inputs 

Each step of an intelligent process is intelligent action.  To be intelligent, the action must be contingent. The contingencies are provided as “inputs” to the logical processing means.  The contingency might be time, a switch position, a fluid level or a logic input.  The parameter involved must be converted to a signal or mechanism that can be “understood” by the machinery.  The conversion device might be a sensor, or a mechanical device or an electrical signal.  Simple examples are the trigger catch mechanism on a mousetrap and a float valve in a toilet.  A gasoline engine has a camshaft to provide a force to open and close the cylinder intake and exhaust valves as needed for the engine to operate.  A home computer has a keyboard and mouse that provides standardized signaling.

Intelligent Processes Require the Use of Machines

Intelligent process steps require the conversion of logical decisions based on information provided by the initial conditions to command and execute specified work, i.e., a machine.

The concept of intelligent processes and machines is confusing because intelligent processes use machines and machines use intelligent processes.  An intelligent process step is the specification of the required task and a machine is the matter/energy entity that performs the intelligent work to accomplish the specified task.

Machines

Intelligent work, which can only be accomplished by a machine[vii], is work that is controlled by embedded intelligence to provide output energy in the right form, at the needed time and profile, to achieve the desired end unattainable by natural causes.

All Machines must have several functionalities:

1. Sensing means. All machines perform an action based on state variables and/or logical inputs that are used to determine work to be performed.  Therefore, the parameters that are involved in the decision-making process must be sensed and signaled to the processing means.  This can mean any combination of:
   1. Passive sensor, a device that has no embedded intelligent functionality, e.g., thermistor, photosensor, strain gage or throttle potentiometer sensor,
   2. Active sensor, a device that does have embedded intelligent functionality, e.g., a servo accelerometer, a radar sensor, an infrared temperature sensor, or a logic output from another machine,
2. Sensor-Processor Signaling means. The signals, or information, must be conveyed to the processing means in a way that the processor can “understand” the information.
3. Logical Processing means. Logical processing is performed on the input signals to determine the action required.
4. Processor-Actuator Signaling means. The “action required” message must be conveyed in a form understandable to the actuator.
5. The actuator is a device, controlled by the signal from the processor, that performs the commanded work. 

These functionalities are implemented by specified arrangements of matter/energy.  Reverse engineering of any process could be systematically organized by first identifying the actions that are used to achieve the specified result; then for each action:

1. identify the initial conditions required for the action,
2. identify the event or intelligent action that starts the new action step,
3. identify the machine that does the intelligent work to complete the action, and,
4. determine how each of the machine functionalities is implemented.

All machines, when working, are running an intelligent process, so the characteristics of an intelligent process apply:  they require specified initial conditions and they must be started by intelligent action.  The concepts described here are hard to visualize by verbal descriptions, so examples of machines of increasing complexity are used as examples to identify the various attributes; initial conditions, start action, sensor(s), signaling means, processor, actuator and power source.

Next Section:  Machine Examples

End Notes

[i] Ibid 14

[ii] Author’s Definition, Intelligence:

1. The ability to make logical choices (logical intelligence)
2. The ability to think, reason, design, and to have self-consciousness (abstract intelligence).

  See other definitions here.

[iii] Note that a specified value can be “do not care.”

[iv] A “most stable equilibrium” may not be a singular state.  For example, molecules in a solution may be jumping between two or more states to maintain a concentration equilibrium when there is more than one product. However, this is the nature of this “state”, and it does not meet the requirement of providing a singular outcome for a given set of input conditions.

[v] Author’s Definition, Process:

1. a series of actions or steps taken designed to achieve a desired end.

  See more definitions here.

Note: This definition is tweaked to eliminate natural processes because intent requires intelligent work.  However, one cannot ignore the use of the term to refer to natural processes such a weather, erosion or even the definition of the second law of thermodynamics as being the natural process of matter and energy moving toward a more stable equilibrium.  However, in this paper, “processes” will always have an adjective to clarify the distinction between an intelligent process, and natural processes.

[vi] There are many intelligent processes that go into a pause or stop mode whereby the stop conditions are the initial conditions needed for restarting.  An example is a reservoir that is filled with water by a pump raising the water from a river.  When the water level drops to a preset level it resets the timer that runs the pump motor which later turns the motor off, resetting the water level to an initial condition for the pause/stop mode. 

[vii] Author’s Definition, Machine

1. An assemblage of parts that performs intelligent work.

  See additional definitions here.