A new methodology for unpacking, defining, discovering and creating Intelligence from scratch – Part 1

After all, what is Intelligence?

Do not be fooled by the obviousness of the question, confusing with your understanding or even the relevance of this word. After all, intelligence has never been so explored by science and fundamental to innovation as it is today, even to the point of people building machines with artificial intelligence.

In this sense, the more we search for answers and definitions for Intelligence, even exploring our brain and mind, in the state of the art, and in the limit of reverse engineering to do so, the more we discover a complexity and diversity of definitions, which in my view becomes necessary be explored to facilitate the alignment of research, hypotheses and discoveries in the most varied areas of knowledge, increasingly digital. In fact, Intelligence itself follows a process of digitization, i.e., a Digital Intelligence, complementing any and all kind of natural intelligence, i.e., an Analog Intelligence.

Actually, this question is not new and some psychologists and researchers have suggested definitions of intelligence such as [1]:

“A very general mental capability that, among other things, involves the ability to reason, plan, solve problems, think abstractly, comprehend complex ideas, learn quickly and learn from experience. It is not merely book learning, a narrow academic skill, or test-taking smarts. Rather, it reflects a broader and deeper capability for comprehending our surroundings—”catching on,” “making sense” of things, or “figuring out” what to do.” from “Mainstream Science on Intelligence” (1994), an op-ed statement in the Wall Street Journal signed by fifty-two researchers (out of 131 total invited to sign).

“Individuals differ from one another in their ability to understand complex ideas, to adapt effectively to the environment, to learn from experience, to engage in various forms of reasoning, to overcome obstacles by taking thought. Although these individual differences can be substantial, they are never entirely consistent: a given person’s intellectual performance will vary on different occasions, in different domains, as judged by different criteria. Concepts of “intelligence” are attempts to clarify and organize this complex set of phenomena. Although considerable clarity has been achieved in some areas, no such conceptualization has yet answered all the important questions, and none commands universal assent. Indeed, when two dozen prominent theorists were recently asked to define intelligence, they gave two dozen, somewhat different, definitions.” from “Intelligence: Knowns and Unknowns” (1995), a report published by the Board of Scientific Affairs of the American Psychological Association.

“To my mind, a human intellectual competence must entail a set of skills of problem solving — enabling the individual to resolve genuine problems or difficulties that he or she encounters and, when appropriate, to create an effective product — and must also entail the potential for finding or creating problems — and thereby laying the groundwork for the acquisition of new knowledge.” from Howard Gardner.

Regarding different types of intelligence, Gardner also defines the Multiple Intelligences theory, opening new fronts of definitions, and at the same time, in my opinion, making the answer even more diverse and complex.

Actually, the Artificial Intelligence pioneer Marvin Minsky, “takes on terms we may all recognize and understand but have a hard time explaining, such as emotions, consciousness, and thinking” [2] and calls these “suitcase words” [3], and if you do a more extensive research, you will find hundreds or perhaps thousands of definitions for something that seems as simple and obvious as Intelligence, as in thesis could induce the initial question of that article.

However, is it possible to answer this question, unpacking, defining, discovering and creating Intelligence?

Maybe, but my ambition is a bit smaller, and my idea here is simply to propose a methodology for it.

Intelligence from scratch, the idea

In my article “The Equation of Wisdom: Measuring the Reality of Artificial Intelligence and its Real Impact on Employability” at https://www.linkedin.com/pulse/equation-wisdom-measuring-reality-artificial-its-real-figurelli/ [4] I proposed and introduced here what I call the equation of wisdom as W = I ^ C, that I created to help measure and address the impact of AI on humanity and our evolution. Actually, I wrote a book about some time ago, and this is a summary of some of these ideas. In my opinion, AI is not AC, and consciousness is key, so Artificial C of Consciousness (including Self-Consciousness or Self-Awareness if you prefer) will become more relevant, and hybrid (like AAC), since machines are far away from this capacity. After all, what is the advantage – or real intelligence (I) – to our evolution, of having an increasingly augmented intelligence, or machines/robots with human-like intelligence, if we do not have an equivalent consciousness (C) of its use?

In this sense, I will begin by presenting my definition of Intelligence, in addition to others “suitcase words” that I consider closely related: Consciousness, Wisdom, Intuition, Evolution, and Innovation.

– Intelligence is the ability to apply the knowledge to meet the objectives.
– Consciousness is the ability to define the objectives from the understanding of the environment and its laws.
– Wisdom is the ability to meet the objectives from the knowledge and the understanding of the environment and its laws.
– Intuition is a hidden and unknown collective wisdom that, sometimes, we have access.
– Evolution is the ability to increase Wisdom.
– Innovation is the ability to accelerate evolution.

And Intelligence, like the small sample I present here, becomes fundamental to several other definitions, further enhancing its relevance, and the need to be “unpacked”.

Also note that, using my proposed equation for wisdom, W = I ^ C, that W, I or C is any kind of Wisdom, Intelligence or Consciousness since this is a very generic equation and that is possible collective/hybrid configurations, such as Machine Intelligence (mI) and Human Consciousness (hC) Universe Intelligence (uI) and Machine Consciousness (mC), etc.

For instance, a complex but viable, future collective/hybrid Wisdom:

W = hI + hC + (mI + aI + nI) hC + hI (mC + uC)

Considering a standard legend for the equation of wisdom as h – human (rational animal), m – machine, a – animal, n – nature, and u – universe.

Therefore, when we think of “unpacking” Intelligence, we must think that it is not just a human property, as it happens in many definitions.

More than that, I think we should think of Intelligence from scratch.

For example, and criticizing my own earlier definition, I do not believe it helps to think of intelligence from scratch, and so I will come up with another definition here for this purpose.

And for this, I’ll start with my vision of Intelligence as fundamental as possible by answering the initial question, which is the one below:

Intelligence is any effect without a random cause.

In other words, the intelligent principle starts from the production and understanding of results different from those generated by mere chance.

Of course you may consider that chance, or random cause, can also be intelligent, but in this case, I think this is the principle of Universal Intelligence, which is not objective to “unpack” here, i.e., I will focus on a pragmatic and scientific vision, involving “only” human, machine, animal, and natural intelligence, which already seems to me a good challenge for our own intelligence.

Intelligence from scratch, the methodology

From this idea I propose of Intelligence, like any effect without a random cause, it is possible to think of a methodology for unpacking, defining, discovering and creating Intelligence from scratch.

Actually, I believe that the production and understanding of results different from those generated by simple chance facilitate the creation of models for Intelligence, opening fields of research in Artificial Intelligence and Digital Evolution.

For this, it is enough to think that everything that you observe in the day to day, and that presents effects without random cause, of some form or another, are results of some Intelligence, despite the type or form that it is, and how complex for us identify its source.

For example, the display you are reading this information, the clothes you are wearing now, the place you are accessing, the light that somehow illuminates this place, the neural networks in your brain — or artificial ones in your cloud — or even the course of a river in nature, are examples of effects without random cause, that is, of Intelligence, that can be unpacked and modeled from scratch.

And I will explore more about it with the continuations of this article.

Rogerio Figurelli – @ 2018-07-15
Post originally published at http://www.4innov.com

[1] Wikipedia, Intelligence – https://en.wikipedia.org/wiki/Intelligence
[2] MIT Technology Review, Minsky on AI’s Future – 2017 – https://www.technologyreview.com/s/407488/minsky-on-ais-future/
[3] Marvin Minsky, The Emotion Machine: Commonsense Thinking, Artificial Intelligence, And The Future Of The Human Mind – 2006
[4] Rogerio Figurelli, The Equation of Wisdom: Measuring the Reality of Artificial Intelligence and its Real Impact on Employability – https://www.linkedin.com/pulse/equation-wisdom-measuring-reality-artificial-its-real-figurelli/


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