Inside Analysis

Artificial Intelligence (AI) – A Less Nebulous Definition

By Russell Ruggiero

There is not a day that goes by when the term “Artificial Intelligence (AI)” is not seen in articles, reports, books, and even on the silver screen. However, what is AI and where does it play in to our day-to-day and in context to robotics, along with neural networks? Related topics also include the Physical vs. Virtual Worlds and Conscious vs. Subconscious, and Information vs. Knowledge. AI is a very broad and often freely thrown around term, which needs to be better defined in what it is and where it can be appropriately applied.

The Future Ecosystem
Fast-forward 100 years into the future, as one would expect, the ecosystem will look much different than the one we know today. It would be logical to assume that Robotics, Neural Networks, and AI will play an ever more important role in our society, but from the outset an “Agnostic” foundation will be needed to enable all these visions to reach their full potential.

Robotics: A branch of technology which deals with the design, construction, operation, and application of robots.
Neural networks: A computer system modeled on the human brain and nervous system.
Artificial Intelligence (AI): A branch of computer science that deals with the simulation of intelligent behavior in computers.

Please Note: One important area that relates to the above concerns Machine Learning which is the study of algorithms and statistical models that computer systems use to perform specific tasks without using explicit instructions, relying on patterns and inference instead. It is not a stretch to say that areas outlined in this section are and will continue to receive a great deal of attention and funding from both the public and private sectors.

Physical vs. Virtual Worlds & Conscious vs. Subconscious
We live in and exist in the physical world, while on occasion interacting with the virtual world as well. For example, a person wants to go out for a walk on a January morning in San Francisco. This person wants to know how to dress (windbreaker or sweater?) before leaving her apartment on Nob Hill. Logging on to her phone, the weather app shows light rain and 56 degrees, which usually means her blue windbreaker and taupe topsiders. In essence, she was able to leverage the information provided by the weather app on her phone to make a rational and logical decision. Now let’s dig a little deeper into both the physical world and the human mind to take on a different path in the decision making process. This person occupies a space within a physical structure which for all purposes is static in nature, but the outside weather pattern is both unpredictable and dynamic. Path One: She leverages the virtual world for information to take the appropriate actions (e.g., clothing, distance, etc.). Path Two: She does not use the weather app, but makes the final decision based on the knowledge gained during her life experiences. She opens a window and peers out to gain a better understanding on what she is dealing with in real-time. A chill, along with a drizzle with ominous clouds in the distance raise some serious red flags. She has seen this type of Bay-Area morning many times before, and feels that keeping the walk short and bringing an umbrella seems like a good idea.
The old expression “think on one’s feet” seems apropos. While virtually sourced information like a weather report is useful in many instances, relying on one’s own intuition can be even more valuable, depending on the situation. Now the debate of Information vs. Knowledge comes into play and is a very important issue when discussing AI.

Information vs. Knowledge
When the word debate is uttered, philosophers that include Thales, Socrates, Plato, and Aristotle from the Golden Age of Greece come to mind. No better work epitomizes this influential genre than the Republic by Plato. This work honestly exposes how information and knowledge are used by humans to make an argument during a casual get together. Question, are their arguments based solely on information gathered and then simply reiterated or is the information acquired synthesized and then applied to make a particular point? In fact it could be both, and that decision is really up to the person making the argument. This question comes into play regarding AI in that the word argument could be replaced by the word action.

A meaningful aspiration revolves around transparency, along with leveraging the countless benefits of technology to help better manage day-to-day activities, while also coping with manmade and natural catastrophic events. Let us for a moment look at comparing Federal Agencies to the Greek City States in regards to Information Technology (IT) and the relation to their respected ecosystems. Most have similar governing structures that follow predefined laws, which are meant to promote order and help form a unified society. It is here where efficient bidirectional and unidirectional information flow plays a critical role. We are currently part of a society where face-to-face interactions are augmented by human to machine – machine to machine – machine to human interactions as well. Nonetheless, the issue of knowledge and how it is managed comes on to center stage.

In theory a Knowledge Management (KM) system should leverage all of the information held within an organization to promote both cohesive internal and external ecosystems. It also, stands to reason that the more transparent the system, the greater the chances of reaching organizational goals and objectives. As a result, not only does there have to be an extensive alignment framework in place, but also a constant and reliable open line of communication at all levels to help steer the effort, which calls for both minor and major adjustments from time to time to reach true KM optimization.

AI Next Steps 

Simply, AI is about leveraging relevant information to make logical and rational decisions. These “decisions” or “actions” will be based on critical factors (e.g., Vision, Mission, Value, Goal, Objective, Stakeholder, and Organizations, etc.) that are provided by parties that share similar goals and interests. Once the relevant information is identified and gathered, then an open-standard like XML Schema Definition (XSD), which is a recommendation of the W3C that specifies how to formally describe the elements in an Extensible Markup Language (XML) document may be used. 

Another key area revolves around Ontologies which is a set of concepts and categories in a subject area or domain that shows their properties and the relation between them. (Oxford).

Other notable W3C efforts include Resource Description Framework (RDF), which provides the foundation for publishing and the linking of data. In addition, important related W3C efforts like Web Ontology Language (OWL) is designed to represent knowledge about things, groups of things, and relations between things. 

How will AI go from concept to reach a reality? Through careful methodical planning and the leveraging of open-standards as well as massive public and private sector investments. Would also like to mention two current important AI related efforts. First, AIKR KAIROS. Second, Strategy Markup Language (StratML). These efforts are both taking an open-standards approach (e.g., ISO, OASIS, W3C, etc.), while aspiring to reach a number of attainable goals that could help to push the AI envelope forward. The AI carrot revolves not only around knowledge, but also on how it is used to make rational and logical decisions.

13 Responses to "Artificial Intelligence (AI) – A Less Nebulous Definition"

  • Gannon (J) Dick
    April 10, 2020 - 2:11 pm Reply

    In the mid-1950’s some kids in Denver had some urgent questions. It may have been a lucky mistake in a phone number, but the result, 65 years later is the same … Public Health authorities track COVID-19 with exactly the same methodology as the North America Air Defense Command (NORAD) tracks Santa Claus. Think about that.

    • Russell Ruggiero
      Russell Ruggiero
      April 10, 2020 - 4:11 pm Reply


      Thank you for the response.

      AI is about identifying, gathering, and the synthesizing of information, which will hopefully be used by computer systems to make rational and logical decisions.

      AIKR KAIROS and StratML are taking the open standards approach via W3C, OASIS, IETF, and ISO.

      Agnostic Ecosystem


      • Gannon (J) Dick
        April 15, 2020 - 1:55 am Reply

        The ecosystem must be both agnostic and not forgetful of Institutional Knowledge, I think. The open standards approach solved this problem completely before web. In some sense we are chasing our “authority tails” saying a jet fighter should fly but a bumble bee should not. We can’t have our AI enabled systems both ways, with the Turing Test in the future, and bumble bees making it all look so easy. It is terrible for morale, for one thing.

        I was the last birth year subject to the Vietnam era Draft Lottery. I have friends who served in the military and friends who did not. Those who did have a rich vocabulary to describe military life. Some of this vocabulary is mere Institutional Knowledge. It is a class of meta data which transfers rather than transforms upon return to civilian life. For example, (Name, State and County) is the new (Name, Rank, Serial Number). The Branch of Service is oddly irrelevant. Once Uncle Sam has taught you military service (or not) he turns you over to the IRS regardless. I am sure you have thanked the Tax Auditor for his service in the past, but this year please make a special effort.

  • Russell Ruggiero
    Russell Ruggiero
    April 16, 2020 - 2:17 pm Reply


    Thank you for the comment, greatly appreciated!

    The bumblebee vs. jet fighter example is quite interesting. Good Points:

    Open Standards: Solves issues relating to “building” things like fasteners for jet planes.

    Knowledge Management: In basic terms, a decision making system.

    You expose a very important topic, how do we in fact ethically and properly manage knowledge?

    Public and Private rules the same or different?


  • Ranjeeth Thunga
    April 19, 2020 - 12:51 am Reply

    Thanks for the article Russ. The connection between interoperable open-standards based systems allow AI algorithms to utilize information from a variety of contexts, some of which might live in different domains, processed and put together in surprising ways to provide us valuable insight.

    That said, what does true insight necessitate?

    That’s an important question — but one point that captures what might be missing in such systems is simply in the word “artificial” itself. Where AI is lacking is that in its present form it does not have the capacity for capture or account for feeling.

    There is a crucial element to intuitive decision-making that necessitates we expound on what we as a conscious entity is actually feeling within us. This is currently beyond our technology based decision-making systems, requiring an deeper exploration and ownership of our true nature as human beings.

    Very much appreciate the article again, as always. This dialog is important…actually essential.

  • Russell Ruggiero
    Russell Ruggiero
    April 20, 2020 - 8:41 am Reply


    Thank you for the insightful and powerful post.

    “Where AI is lacking is that in its present form it does not have the capacity for capture or account for feeling.”

    Very eloquently put.

    There is little doubt that our society is experiencing a dwindling of social skills. This behavior can be directly related to humans being fixated on screens that contain content.

    Case in point: Eyes fixated on a small screen (e.g
    , smartphone, tablet, etc.) and small speakers inserted into our ears.

    People are often seen operating in silos, which permeates behavior that is becoming more and more prevalent.

    Are we humans currently experiencing an anesthetizing of our emotions?

    If this scenario holds true, then there may be a convergence in the behavior between humans and AI.

    Please feel free to share your thoughts.


  • Matthew Harang
    April 25, 2020 - 1:35 pm Reply

    Wow, excellent work here Russ. This is a timely and relevant piece. The connection you make between these subjects is very important to understanding the future of AI and technology in general. My feeling is that, conceptually and figuratively, our brains are becoming more and more digitized as we increase our reliance on technology. The incessant connection to our smart phones, especially in the younger generations is specifically interesting and concerning to some degree. People are spending less and less time disconnected from their phones, internet and social media; that means less time connected to the natural/human world. There is a lack of research about the effects of this type of lifestyle on our brains and bodies. There is no doubt that it affects us mentally and emotionally. At the same time, technology is becoming more and more useful and intelligent, which only increases our need, perceived or real to “stay connected.” The usefulness of “smart” technology in general cannot be understated. It will enable us to continue to work “smarter not harder.” It’s very insightful that you mention knowledge management and not just information management because AI will become increasingly useful in KM as many businesses move towards embracing Agile methodologies like knowledge sharing, transparency and self-organizing teams. As a society, we have to figure out where and how the boundaries must be set, finding a sweet spot of utilization of AI and smart tech. Interesting times are ahead as innovations continue.

  • Russell Ruggiero
    Russell Ruggiero
    April 26, 2020 - 9:37 am Reply


    Thank you for the outstanding post.

    You point out the difference between information management vs. knowledge management.

    Very important.

    How does structured and unstructured data play into the AI equation?

    What is it we are trying to build and for what purpose?

    Again, thank you.


  • Ranjeeth Thunga
    April 30, 2020 - 4:04 am Reply

    Good to hear from both of you.

    Both AI and our tech systems seem to be built on the premise that our emotions are not relevant. Anesthesization, so to speak, may simply be a byproduct of this dismissive attitude, if you will, towards our human experience plays in all of this (except as a factor to manipulate).

    So it seems we’re currently barking up the wrong tree — as far as human fulfillment is concerned. Let’s hope to and do our part to course correct.

  • Russell Ruggiero
    Russell Ruggiero
    April 30, 2020 - 6:05 pm Reply


    We are still trying to figure out how technology plays in Society.

    The term is not only misused, but over used.

    Evolutionary or Revolutionary?

    Money making or for the greater good?

    We really need to refocus and see how technology can benefit mankind.

    Best wishes,


    • Rex Brooks
      May 5, 2020 - 3:21 pm Reply

      I decided to go ahead and respond despite the incompleteness of my research lest I lose track of my thoughts on the topic. It seems to me that what is being discussed in this thread is more along the lines of assistance than independent input on any given topic or decision-making situation. This is not to suggest that a really good assistant would not be worth its weight in diamonds. In fact, when we really get one, I want to be first in line to get it. Unfortunately, right now I don’t think any of the tools really measure up. And as for genuine AI, I think we’re still years away, although I don’t think it will sink in until we’re looking back on today from a longer perspective.

      That also doesn’t mean it isn’t worth careful examination in today’s upended world. We really need it right now, but I wouldn’t bet the farm on any of the current models.

      That said, I agree with almost all of your points and I hope we can synthesize a new viewpoint here that combines the strength and clarity of ontologically-unified semantics with standards like XML, JSON, RDF, OWL et al along with fundamental common sense, which is, unfortunately, anything but common. Let’s keep working on it. All these reams of research will show up in my next writing projects, which I hope to share with you, as it comes along.

  • Russell Ruggiero
    Russell Ruggiero
    May 6, 2020 - 1:24 am Reply

    Hi Rex,

    Thank you for the kind words and support, greatly appreciated.

    We really have to major hurdles regarding AI.

    1) How to build?
    2) What to build?

    You have the “can use any data group” and you have another camp trying to imbed identifiers into elements. Both have their merits and drawbacks.

    In the “Little Sandbox Theory” we look at adding critical identifiers (e.g., mission, vision, value, stakeholders, etc.) with an open standard like StratML Part One.

    Once we “find” and “gather” then other open standards like XSD come into play regarding structure.

    Now once we have all this identifiable structured data what do we do with it?

    Enter a another set of open standards, RDF/OWL, which try to address the “relationship” aspect of the equation, along with Ontologies.

    The path outlined here is one possible solution in finding the path to true AI.

    As for what to build? Another discussion altogether!

    Again, thank you for the wonderful post, and support.


  • Ranjeeth Thunga
    May 7, 2020 - 4:41 pm Reply

    I like that point Rex about common sense, which is necessary to both create and demonstrate in future AI models. In addition to the important fleshing out of “how to build” and even “what to build” is the question of “where are we going?” That’s certainly an area of much more exploration, though I do feel it does require a utterly different paradigm from those offered in our current education, business, and technology landscape.

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