These terminologies are presented in the order of their first appearance within Chapters 8.1 and 10.0, of this documentation, instead of an alphabetical order. This is for highlighting the logical dependency of subsequent terms, on explanations and meanings of prior terms and phrases.
A mathematical graph with a representation of cognizable concepts, along with their intertwined relationships. The graph of identifiable concepts are laid out, and mapped along two orthogonal axes of a table. The tabulated form can then be utilized as a starting point for creating, as well as a quality control template for evaluating, engineered systems.
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The first axis denotes the semantic continuum of Part-Whole relationships, from a modal logic and systems perspective.
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The second axis denotes the continuum of tangible (i.e. concrete and specific), versus, the abstract (i.e. intangible and generic) nature of each individuated concept being graphed, with respect to human sense organs and cognitive faculties, as per the science of human factors and ergonomics.
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Example:
Unstructured list of concepts: brand image, vehicle, engine, driverless, Toyota, algorithm, trustworthy, cost, factory, V12 Engine, Lamborghini, durable, ethical norms, mileage. Hierarchical tabulation: ▲ Abstract-Whole Abstract│ ┌───────────────┐ (purpose or aim) (general)│ │ Ethical norms │ │ └───────────────┘ │ │ ┌────────────┐ ┌─────────────┐ │ │ Driverless │ │ Brand image │ │ └────────────┘ └─────────────┘ │ ┌─────────────┐ │ │ Lamborghini │ ┌─────────────┐ │ ├─────────────┤ │ Trustworthy │ │ │ Toyota │ └─────────────┘ │ └─────────────┘ │ ┌───────────┐ ┌─────────┐ │ │ Algorithm │ │ Vehicle │ │ └───────────┘ ┌────────────┐ └─────────┘ │ │ Durability │ │ └────────────┘ │ │ ┌──────────┐ ┌────────────┐ │ │ Engine │ │ Mileage │ │ └──────────┘ └────────────┘ │ │ ┌────────────┐ ┌─────────┐ │ │ V12 Engine │ │ Factory │ Tangible│ └────────────┘ └─────────┘ (specific)│ └───────────────────────────────────────────────────────────────────────────► Part Whole (component) (assembly) -
In the above diagram:
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When we track the concepts along the diagonal bandwidth, from Tangible-Parts towards an Abstract-Whole, we can conveniently notice that a "Driverless-Lamborghini" would be pointless, because it wouldn't add any value to Lamborghini's brand image of, "experiencing the excitement of being in the driver's seat of a super car."
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However, a "Driverless-Toyota-Vehicle" could be a worthwhile output from an industrial factory for, "experiencing the serenity of not being in the driver's seat of a taxi, or a delivery van."
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It can be estimated that a method for encouraging "consumer confidence" in the generalized concept of a driverless vehicle, as well as in each specific instance of a produced drone model, would be borne out of a set of design and business decisions made by R&D groups involving manufacturing companies. Such decisions would invariably need to accommodate concepts like a particular model's rated durability and type of engine, along with many more concepts like: the model's available accessories, repair costs, insurance policies, and replacement orders from dealerships. It can also be surmised that those design and business decisions would naturally be dependent on internal, quantitative fiscal goals of each company within an overall supply chain, and even on qualitative concepts like "consumer satisfaction" that haven't been represented in the current iteration, of the given example of an Abstraction Hierarchy.
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Even a systemic overhaul of an entire geographic region's transport infrastructure could be achievable, for stimulating the economy, and for improving ecological sustainability, if the appropriate level of trustworthiness were to be instilled in the minds of prospective customers, for purchasing and relying on particular models of cost-effective driverless vehicles.
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So, when considering the question, "Why is the concept of 'ethical norms' an Abstract-Part of a system?", the more pertinent question would be, "How can ethical norms not be a part of human ecology, where ethical behavior of agents and agencies, are an expected, practical, and tangible requirement of everyday life?"
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This method of tabulation can account for anthropomorphic, cultural, lexical, and ethnographic connotations associated with each identifiable concept, wherein concepts are represented as mathematical objects, with graph based nodes and edges, in a hierarchical vector space. Doing so is necessary for building natural language processing algorithms, and other types of programmable algorithms for systems driven by goal oriented artificial intelligence (AI). AI algorithms can utilize a given graph based lexicon derived from an Abstraction Hierarchy, i.e. a relational database of words.
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Canonical Abstraction Hierarchies and databases are crafted by skilled researchers, engineers, and technicians, to train an AI for performing various automated or semi-automated tasks, and functions, within a physical environment.
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The part-whole relationships among tabulated or graphically represented concepts are measurable, objective, and provable via set theoretic principles. The degree of abstractness of a tabulated concept, is subjective and dependent on the knowledge, experience, and expertise of the craftsperson who authors and manually creates a particular instance of an Abstraction Hierarchy. Thus, the objective as well as subjective aspects of real-world human experiences, pertaining to a field of study and work, can be modeled or represented, by single or collaborating authors of Abstraction Hierarchies.
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Abstraction Hierarchies in the form of tables or graphs, form the ground truth and the basis for subsequent categorization as well as classification algorithms, in an AI training schedule, or pipeline. As such, these truth tables are necessary for producing codified software components of systems driven by an AI, like unmanned vehicles i.e. drones. Such graphical tables are also necessary for creating user manuals, safety protocols, and addressing performance issues of the automation.
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An Abstraction Hierarchy can recursively describe itself, its contents, and also its construction techniques. That is, the concepts of abstractions, hierarchies, and of the mathematical operations needed for constructing an Abstraction Hierarchy (using a given collection of other concepts that need to be classified or categorized), can be described with an Abstraction Hierarchy.
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In this manner, Abstraction Hierarchies serve as an indispensable tool for doing feasibility and impact studies, and can also be used for creating a bill of materials for a product, designing user-interaction maps, evaluating design alternatives, conducting cost-benefit analyses, and even for making legally defensible business decisions from available options.
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From the lens of operation's research and organizational psychology: Abstraction Hierarchies are used for creating and evaluating trained behaviors of the managers, supervisors, and operators who purchase, utilize, and operate a technological system within a domain.
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Therefore, the accuracy, precision, concurrency, closure, and efficiency of a programmable and engineered system, cannot be properly defined or evaluated, without the art and science of methodical tabulations of "concepts," being arranged in certain regularized hierarchical structures.
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The most important caveat to be mindful of, is the fact that the art of creating different Abstraction Hierarchies, results in engineered or engineering systems that have different sets of functional priorities. Those priorities driven by a business minded person through an AI, might not prioritize the well being of end-users, bystanders, earthly species, habitats, and of vulnerable people impacted by the system, over their own self-centered pecuniary motives.
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Interestingly, an Abstraction Hierarchy with all conceivable concepts in every possible language, constructs an "Ontology" like the one being built by Google and OpenAI.
- An ontology that can define "the concept of a concept," along with other things observable in the universe, usually ends up getting labeled as an "Upper Ontology" by philosophers and computer scientists.
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Here are additional references and examples of Abstraction Hierarchy's usage in creating and evaluating automated systems: https://scholar.google.com/citations?user=yFs-PHYAAAAJ
A framework for creating an analytical description of the physical, historical, sociological, political, economic and technological aspects of an observable environment — for the purposes of doing safe, value added, legal, and earnest human labor within the described environment.
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Such an analytical description typically involves an Abstraction Hierarchy that categorically describes each and every entity of elemental, and ensemble nature of complex systems (like power plants and airports), that living and non-living entities can be exposed to, while a particular context of work is being carried out in the described environment.
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A Work Domain Analysis, is necessary for identifying hazards and faults present within systems that owners, operators, and bystanders can be exposed to, in an observed ecology. Such hazards and faults naturally lead to liabilities, but can also give way to zero-day-hacks of susceptible and improperly managed systems. Work Domain Analysis consequently provides methods and policies for mitigating risks.
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This approach to analysis and decision making is useful in identifying the type of work that can, and ought to be done, in environments like: "online spaces" generated by wide-area connectivity of internet enabled devices (IoT), permafrost, deep ocean, and outer space. These types of environments are being newly explored, especially by military and commercial operators seeking a sustainable foothold in those subdomains.
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Here is a primer on the subject: "Work Domain Analysis Concepts, Guidelines, and Cases" by Neelam Naikar
Ecological Interface Design facilitates human-human, and human-machine interactions within an "ecology." The term ecology includes anthropological and physical facets of an environment where a network of resources, devices, machines, policies, and human beings co-exist.
A study and research of ecological relationships among co-existing networks yields constraints i.e. rules that govern the behavior of those networks. These constraints are to be adhered to, by persons and agencies existing in the ecology, for the sake of preserving or enhancing the health, productivity, performance, evolution, and sustainability of those networks.
Intentionally displaying discovered constraints or rules, in specific and timely ways to the "end-users" and persons impacted by a system, guides those end-users and persons towards becoming well informed, and also towards formulating viable goals, behaviors, and activities. The technological and engineering based design process for creating and deploying policies, tools, and training methods for conveying said constraints to various people interacting with a system, is called Ecological Interface Design.
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Among Ecological Interface Designers, constraints and boundaries that already exist, and can potentially exist within an ecology, are colloquially known as "affordences." Though the word is unlikely to be found in any English dictionary, it has exactly the same meaning and usage as "sanctions." An affordence or a sanction, restricts or enables particular degrees of freedom that an agent can have, in order to think or act, within an ecology.
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The main aim of Ecological Interface Design is to structure an agent's intentions that can permeate in an ecology, via synthetic guide rails contrived by human beings, like philosophical principles, social norms, or conventions; and also via natural ones like physical laws of thermodynamics, or electromagnetism. In this design process, the value or worth of any particular set of guiding structures, is acknowledged as being culturally dependent, and also as being contextually bounded to "the end-user" of the built interface.
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For engineering purposes, the meaning of the word end-user is often the same as the technical, and legally warranted usage of the concept of end-user in contractual agreements called, "End-user License Agreement (EULA)" for goods or services supplied by an agency, to a consenting consumer.
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Examples on how to build an Abstraction Hierarchy, when conducting a Work Domain Analysis, are explained within this article on Ecological Interface Design: https://en.wikipedia.org/wiki/Ecological_interface_design
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Some more details about how Ecological Interface Design plays an integral role in industrial, and systems engineering, is explained here: https://en.wikipedia.org/wiki/Ecological_interface_design
Activities carried out by regimented armed forces personnel and staff, which can be legally considered as being: morally and ethically earnest, and legitimate.
An appropriate and internationally codified definition of military work is required for answering questions like:
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How are projections of military power and use of forces, different from extortion or armed robbery; especially, when they are used for subduing a country into submissively accepting unfair and inequitable trade deals?
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Is the ultimate purpose of military work only to annex territories and enslave other nations as client states, and to then use captured peoples as guinea pigs for every type of experimentation?
The different types of physical domains, where a military unit can carry out a set of actions that constitute human labor, are typically defined as land, sea, air, and outer space.
The concept of "cybernetic domain" was given a doctrinal definition via the framework of Work Domain Analysis as:
The overall physical ensemble, of all regions of land, sea, air and outer space, where human communication through any type of signaling is feasible for carrying out a set of activities.
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For the military, the cyber-domain (i.e. the cybernetic domain) isn't merely the aspect of day-to-day reality that involves electronic communications, it is the whole of reality across every measurable span of space and time, that involves any communicability of physical information, between any and all communicating entities including human beings, and engineered devices.
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Without such a definition of the cyber-domain, the concepts of cyber-warfare, and cyber-attacks remain ill-defined. And with such a definition of the cyber-domain, cyber-warfare has come to include genetic modification, social engineering, computer networking, and multimedia based attacks on supervised as well as unsupervised systems.
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So, defending critical infrastructure systems or any other envelop of habitation from cyber-attacks, naturally requires an astute understanding of how strategies and tactics for cyber-attacks can be developed, and orchestrated.
As such, through this framework of definitions, the military can subsume all human activities, and assert superior authority over all categories and classes of actions, that can be performed by any conceivable agency or organization, including the judiciary. It is however, unnecessary for any military unit to be involved in steering a civilian agency or a group.
What can be done, need not be what ought to be done.
Accepted and implemented international laws governing how warfare is to be initialized and conducted.
These laws include Rules of Engagement (ROE) or Rules for the Use of Force (RUF), within domestic as well as international conflicts.
Many of the accepted laws and regulations concerning war, are emulated by treaties like the successive series of Geneva and Hague conventions.
These types of conventions were not meant to be taken lightly or scoffed at, even though they aren't exhaustive and complete: https://en.wikipedia.org/wiki/Law_of_war#International_treaties_on_the_laws_of_war
Abbreviations:
AI - Artificial Intelligence
R&D - Research and Development
ROE - Rules of Engagement
RUF - Rules for the Use of Force