Sunday, December 24, 2017

On a definition of AI

or  :)    ==>>
The copy of this post has been sent to a professional magazine.
The response was controversial :), which I loved!
Dear Dr. Voroshilov:
We enjoyed your letter, but the board declines to publish it because they thought it would be too controversial.
Editor, Journal of Experimental & Theoretical Artificial Intelligence
makes me feel proud!

On a definition of AI

Ask an AI professional: “What is your definition of Artificial Intelligence?”
At first you will hear a description of many functions and abilities of intelligent beings (us).
If you keep insisting: “No, I don’t need a description of it, I want a definition”; the best answer you get is … (“I’ll keep you in suspense”, but if you want to know the answer immediately, just scroll down the page).
Definitions represent the skeleton of a science (any science).
If a research field does not have clear and operating definitions for all the fundamental terms it uses, it is not yet a true science, at the best, it is a science in making.
Giving a good definition is very important, and not always easy. Take, for example, a famous tale about Plato and Diogenes, which says that “when Plato gave the tongue-in-cheek definition of man as "featherless bipeds," Diogenes plucked a chicken and brought it into Plato's Academy, saying, "Behold! I've brought you a man"” (
Nowadays, stories about new AI achievements are everywhere. But what is AI? What is a definition of it?
The article “Artificial Intelligence” in Encyclopedia Britannica is composed of about 8000 words. It can be divided in three major parts.
The first part (the shortest one) simply says that artificial intelligence is like human intelligence but artificially manufactured. 
The second part is a shorter version of the article about human Intelligence.
The third part describes various technical approaches to constricting AI.
The clearest and actual definition of AI is provided in the first part, i.e. AI is artificially manufactured system which can do what HI (human intelligence) can.
I think this is the best approach to define any artificial object which has a biological counterpart ("an artificial arm" for example, is "an artificially made arm"), because it fits the Occam's razor criterion.
That leads us to search for a definition of intelligence, in general (HI represents a biological realization of it).
The article “Human Intelligence” in Encyclopedia Britannica is composed of about 9000 words. It describes various approach to understanding what intelligence is, its aspects, elements, properties, manifestations.
But this article does not give a clear definition of intelligence.
Here are the first two sentences from the article, quote:
Human intelligence, mental quality that consists of the abilities to learn from experience, adapt to new situations, understand and handle abstract concepts, and use knowledge to manipulate one’s environment.
Much of the excitement among investigators in the field of intelligence derives from their attempts to determine exactly what intelligence is.”
The article provides a short description for many various attempts, but does not offer one description of what intelligence is, which would dominate the field.
Without having a formal definition of AI, searching for AI would be like “go there don’t know where, and find that don’t know what” (this is what Tsar said to Andrei the Solder, according to a famous Russian tale).
So, every researcher in the field of AI development has some definition of AI (because, clearly, they know "that, what they want to find").
But without having one commonly accepted definition of intelligence (or anything else, for that matter) every researcher who is trying to construct AI (or anything else, for that matter) can base the attempts on the description which fits the best his or her own views.
Of course, the majority of actors in the field base their actions on something they all have in common (that common part defines the field).
And that common part which defines the field of AI is patterns.
Everyone in the field accepts, as the basis for all R&D activities, the fact that intelligence does not exist without pattern recognition. But as the result, many researches in the field of AI shrank intelligence to pattern recognition, i.e. they simple made intelligence and pattern recognition equal: intelligence is pattern recognition.
BTW: it happens every time when the process of the development of a definition of an object is based on listing the set of attributes the object has or doesn't have ("men are featherless bipeds").
Of course, deep inside they all know that this approach is wrong (or at least insufficient), but without having a definition of intelligence, that is the best they can do.
And we all know that intelligence (at least HI) is more than just an ability to recognize or produce patterns, because animals also can recognize patters. Even more, animal world provides many examples of complicated pattern development (e.g. bees, termites, beavers, spiders).
As an expert and a professional in HI, I have been searching for a simple, clear, workable, operational definition of intelligence (BTW: another question about definitions - what is the difference between an “expert” and a “professional”?).
In 2017 this search has finally come to an end.
This is my definition of intelligence:
Intelligence is the property of a system; the mission, the reason for its existence, and the core ability of intelligence is creating solutions to problems which have never been solved before (by that system).
© Valentin Voroshilov, 2017
All other aspects of intelligence (heavily discussed in literature, and artfully presented in Encyclopedia Britannica) play their roles, and take their places as devices, components, abilities, organs, functions required for intelligence to exist, perform, and achieve its goals, fulfill its mission - creating, again and again, a solution to a problem which has never been solved before. 
Many times one an can hear or read that "intelligence is an ability to solve problems". But this statement is not operational enough, and not differentiative enough to be a definition. Digging trenches solves problems. Or name numerous of other activities which solve problems but not require intelligence. Or one (or even animal) can be drilled how to solve a specific problem when that problem will arise - also no intelligence is involved. My definition is operational and differentiative; it allows to separate intelligent activities from acquired via drilling practices.
BTW: I have a clear vision of how AI can be used to study and improve learning and teaching practices on a large scale. In particular, I have developed a specific strategy for using advances in AI to developing a new type of content knowledge measuring instruments in physics, mathematics, and chemistry. Based on my experience of teaching problem-solving and knowledge of how mind learns, I also envision a specific strategy which will lead to the development of AI capable of solving physics problems, potentially even win a physics competition, and then be capable of becoming an artificial physics teacher (no the best one, but better than many current ones).
Someone might ask, how come that professionals in the field could not come up with an operational definition of intelligence, but a physics teacher could?
First, I am not just any physics teacher. I am a very good physics teacher who for a long period of time has been successfully using his own natural human intelligence.
For example, this is an excerpt from one of many student evaluations: “I hated physics before taking this course, and now after taking both 105 and 106 with Mr. V, I actually really enjoy it. He is one of the best teachers I've ever had. Thank you” (ten more pages on this link :) ).
This is what teachers can do! From the NASA's "Brief History of Rockets"
“In 1898, a Russian schoolteacher, Konstantin Tsiolkovsky (1857-1935), proposed the idea of space exploration by rocket. In a report he published in 1903, Tsiolkovsky suggested the use of liquid propellants for rockets in order to achieve greater range. Tsiolkovsky stated that the speed and range of a rocket were limited only by the exhaust velocity of escaping gases. For his ideas, careful research, and great vision, Tsiolkovsky has been called the father of modern astronautics.”
And third, for business minded people, keep in mind, if it wasn't for Steve Wozniak, the worlds would most probably never knew Steve Jobs.
Back to our topic.
When the host of intelligence (e.g. a human person) creates a solution to a problem the host has never solved before (or has no memory of that) but that problem has been solved in the past by other host(s), the intelligence plays only local role – for that host only.
But when the host of intelligence (e.g. a human person) creates a solution to a problem NO host has ever solved before, the result has a global value – for the whole assembly of hosts (e.g. human society).
BTW: (a) this definition of AI should be sufficient to design the Turing test (which will be possible only under assumption that the machine will not be able to lie).
(b) teaching creativity (a.k.a. critical thinking, creative thinking, lateral thinking, inventiveness) is “simply” teaching students how to create solutions to problems they have never solved before, i.e. teaching students how to be intelligent (what I have been successfully doing for many years:
Naturally, my definition of AI is based on a subset of definition, for example, on a specific view on what a problem is, what does it mean “to solve a problem”, and much more (that is why I have been intensely publishing all my blogs).
In this piece, I only also want to present the difference between a problem and a task:
1. When someone needs to achieve a goal, and knows what actions to perform in order to achieve it, it is not a problem it is a task.
2. When someone needs to achieve a goal, and does NOT know what actions to perform in order to achieve it, that IS a problem.
The definitions above represent the simplest description of “a task” and “a problem”, but already can be used as the means for differentiating intelligent actions from routine actions.
There is one more question, the answer to which affects the whole discussion: “What is a scientific definition of “a scientific definition”?”.
I like to ask my students a short version of it: “What is a definition of “a definition”?”, and it always makes them think hard, and generates a discussion.
Everyone is welcome to join this discussion (BTW: this discussion is essential, crucial for the final choice of the actual definition).
So, what is the meaning of AI – as a symbol (abbreviation)?
Well, first and foremost it is the ultimate goal of the R&D in the field of AI development.
But currently, it is a brilliant marketing instrument, helping to promote the R&D in the field. The actual abbreviation should be APRS for an Artificial Pattern Recognition System, but AI of course is much cooler!

Ask an AI professional: “What is your definition of Artificial Intelligence?”
At first you will hear a description of many functions and abilities of intelligent beings (us). Basically, AI is described as an artificial human, which is not an actual definition.
If you keep insisting: “No, I don’t need a description of it, I want a definition”; the best answer you get is: “AI is an artificially manufactured pattern recognition system which can expand/advance/increase/broaden the scope of its own functions without human interference”.
This definition accurately describes human intelligence.
However, this definition also accurately describes animal behavior.
Everyone who is fine with being on the same level with animals can keep using that definition.
Otherwise, I suggest switching to mine.
BTW: there are at least two simple ways out of this conundrum. First is introducing two definitions:
1. General Intelligence (GI) is a pattern recognition system which can expand/advance/increase/broaden the scope of its own functions without interference from other intelligent systems (incorporates all animals, including humans).
2. Human Intelligence (HI, or for a broader use – Intelligent Intelligence, or Logical Intelligence, or Ultimate Intelligence) is the property/feature of a system with the mission, the reason for its existence, and the core ability of creating solutions to problems which have never been solved before (by that system).
In that case, the current meaning of AI becomes the equivalent of AGI (artificial GI), which includes HI and another “A”I (animal I).
The Ultimate AI, which does not yet exist, but heavily described as “almost here”, is AHI (artificial HI).
The second is also introducing two definitions:
i.e. keep the word "Intelligence" for "an ability to solve problems which have never been solved before (by the host).", but name the animal behavior differently, e.g. "Animal Intelligence", or "Pre-Intelligence", or "Quasi-Intelligence", "Pseudo-Intelligence", "Intelligent Orientation". Of course, there is some overlapping between the two, some gray area when intelligent species look acting like animals, and animals look acting like intelligent species - that is inevitable - but it does not make the definition less useful.
After epilogue: or The part which has no name because it goes after the EPILOGUE which is by the definition is the last part of a written piece
The distinct, unique, crucial, necessary and sufficient attribute, feature, property, expression of intelligence is (wait for it) – a DOUBT.
Creating a solution to a problem which have never been solved before inevitably leads to some uncertainties, to the situations when there is no (not exists) purely logical reasoning leading to the answer, to the goal, to the expected result. In this situation an intelligent subject always KNOWS that this is the time when the only possible action is to “go with the gut”, “to flip a coin”. The result – “do this” – is based on fluctuations in the neural network of networks called a brain. This is what no current so called “AI” can do. Current “AI” has no doubts. It makes the decision (“this is this face”, “this is this word”, “this is this …”) based on the training it had. The better its training was, the less mistakes it makes (e.g. looking at a banana and seeing a face). But the current “AI” never doubts its choices; currently an HI (human intelligence) needs to interfere to check “AI”s decisions (if only HI was always smarter than “AI”:  
Until an artificial brain learns how to process fluctuations in its network, artificial intelligence will not be an actual intelligence but merely an efficient pattern recognition device.
But even in the such developed field as visual pattern recognition current "AI" makes silly mistakes. Let's say "AI" is trained to recognize a banana. It cannot see the difference between an actual banana and the picture of a banana. Because that would require to understand perspective vision. A coder can try to write a mathematical model for that. But in order to learn the difference between a picture of an object and the object AI needs to do what children do when they learn the world; it needs to see, walk, and touch things, and to learn the correlations between actions and timing of the feelings. This is way ahead of today. That is why I also added another post on the matter: "Relax, the real AI is not coming any soon".

Appendix I: a conversation with a professional
Recently I was informed about a 2007 paper, containing the survey of various definitions of Intelligence ( The list is very impressive. I found two which could be seen as a definition, but both are relatively similar to mine.
"Intelligence ... is an ability ... to solve new problems" // W.V. Bingham. Aptitudes and aptitude testing. Harper & Brothers, New York, 1937. 
I would say my definitions includes this one, but make a more specific statement, which makes it more operational.
Another one was "Intelligence ... is an ability ... to achieve goals" (belongs to the two authors of the paper).
I would argue, that essentially that translates into my definition, with the goal "to achieve the solution constructed to a problem which have never been solved before”, which makes my definition clearer and more operational.
I sent an email, in which I describe my view. In an email back I was pointed at the importance of "being able to solve problems in various environments (solving wide range of problems, achieving wide range of goals)". 
I responded that I would not consider an additional description, namely: "wide range” - as an important part of the definition of intelligence, due to the following reasons: 
1. from my point of view that is implied and obvious.
2. a definition of something, including Intelligence, should be concise, sufficient on its own, without the need for additional explanation of a possible interpretation.
3. the host of intelligence does NOT have to use it wide, the definition should allow to observe (measure, assess) one individual and make a conclusion if the host has or doesn’t have Intelligence (e.g. Turing tests).
4. Intelligence should not depend on a specific field of action; the property/ability/feature called “Intelligence” should be “field-independent”, which makes it “field-universal”, meaning, if it works in one field, it will work any any/every field. The ability to create solutions to problems which have never been solved before is exactly of that type.
"Achieving a goal" (in any practical or theoretical field) when you KNOW how to achieve it is very much different from a situation when you DON'T know how to achieve it and have to develop/design the solution (procedure, protocol, device); that ability is the central core of HI, or “I” in general (please, refer again to my differentiation between "a problem" and "a task").   
Speaking about the definition of AI, my view is that, no matter what definition of Intelligence is used, Machine “I”, or AI, it always means the same - Intelligence developed artificially. There is no need for a special definition (like artificial arm is an artificially made arm). It may make sense for internal use between AI developers, but for general public, practitioners, educators “A” just literally means "Artificial". Although, that would require a discussion about the meaning of word "definition", including what is its purpose (and history, e.g. what Aristotle meant by a “definition”, etc.).
In conclusion I made a point that if a commonly accepted definition of Intelligence existed, it would be presented in the corresponded article in Encyclopedia Britannica. Since that is not a case, the question is still open, and the discussion remains vital. 
NB: This response of mine effectively concluded our communication; since then I have not heard back a word. As an expert in Human Intelligence, which includes human psychology, I know the reason for having our communication severed. I shook the ego of the authors of the paper. They had a nice construct of what they called "Intelligence", but some guy from the streets, someone with no name, no recognition, poked and made a big hole in that construct. So, they did what most people do in this situation, they pretended that nothing happened. Of course, those people are not idiots. In their minds they continue to mull over our conversation, their argument, my counterarguments. Eventually they will come up with their new definition of Intelligence, one which will have something from their old definition but will also have crucial elements of mine, and they will think that they came up with this new definition completely on their own. Which is fine. All this AI stuff for me is just a hobby on a side (at least for now). Once in a while I just like poking a sleeping bear and see what happened.  So far 100 % of my expectations turned out to be correct.
Appendix II: another conversation with another professional (with a slight touch)
Dear Valentin,
I'm not so so keen on definitions. You know the old challenge, can you define a game?

Dear Dr. …,
thank you very much for your note.
I follow the General Theory of Human Activity:
* science is one of human practices;
* as such it evolves, has phases and stages; and levels;
* the direction of evolution of science does not depend on the actual field;
* there is a stage when people in the field do not have commonly accepted definitions;
* there is a stage (the higher one) when people in the field have developed commonly accepted definitions;
* this transition is inevitable and unavoidable;
* and, of course, in every science, there are terms which cannot be defined (the root terms), but it does not mean nothing can be defined, on the contrary, everything which can be defined needs to be defined;
* and if something (mass, charge, game, intelligence) has been defined, it does not mean that definition will not evolve in the future;
* one of the goals of a scientific methodology is to separate the categories in the field as definable and non-definable.
Since within any linguistic system, including science, not all terms are definable, classifying terms as definable or undefinable is the part of the job of the scientists in the field.  What to do with undefinable terms (and maybe "game" is one of such) is also the part of the discussion. But the existence of undefinable terms logically does not lead to the non-existence of definitions (and I believe my definition of intelligence is a definition).
At a certain point it all goes down to personal beliefs (I have more on this matter here:
On your challenge, for me personally, a game is:
1. human activity (or in general, intelligent activity)
2. the participant or participants can choose to participate or not in that activity without damaging consequences
3. the participant or participants chose to follow specific and the same rules
4. there is a specific rule or rules (a criterion) which describe when the game is finished and what is the result
5. after the game the participants can return essential to the pre-game state, i.e. the game does not have a drastic effect on the participants’ life (clearly, word “drastic” give a wide leeway for interpretation, but this statement works as the first iteration).
From my view, this is not yet a definition, because these conditions are necessary, but not sufficiently sufficient; but it grasps the essence of what a game is.
I would be happy to have coffee with you some time, if you have such an opportunity.
BTW: so far no coffee
P.S. After the letter was sent I came up with this shortest sentence: a game is (1) a pretended life (in that what people call "life" they would not do "it"); or (2) a life pretended to look like a game (in that what people call "life" they want do "it" but do not want to show that they want).
Well, I was not the first one to venture a similar sentiment: "Life is a theater".
Interesting fact: one can replace word "art" in the first quote with basically anything ("teaching", "maganing", researching", ...) and it still will stand!
P.P.S. After I have developed my own definition of game, and its shortest version (the sentence in blue) I, naturally, looked it up online. They all are basically say that a game is a play or a competition, or ..., and there is a list of possible activities, which is technically not a definition. 
Appendix III: on the general structure of a problem-solving process
The general structure of a problem-solving process, or PSP (i.e. the process required to solve a problem; i.e. the process required to create a solution to a problem), does NOT depend on the problem; in particular, it does not depend on the field to which the problem belongs.
That means that (1) one needs to learn how to design the PSP in one field - and the BEST field to do that would be physics (here is why: (A) a text,; (B) slides,, slides 59-61 point at a relationship between cyber thinking and thinking; which in greater details is described in "How much of "cyber" in "cyberthinking"?"); 
then (2) one needs to learn how to transfer that skill to solve problems in another field (does not matter which one), 
and (3) after that the one will be able to transfer that problem solving skill (PSS)  to ANY field
This is the description of the fundamental basis for teaching with establishing reliable transfer of knowledge (not presented in literature, but essentially based on the Vygotsky theory of a Zone of Proximal Development; e.g. at; more at;).
Specific structure of PSP in physics is described at
On specific thought process in physics:
Appendix IV
On Wednesday, 02/14/2018, I was listening live a Congressional hearing on AI (
Everyone who has a slightest interest in AI should do it, too. I would like to point at only three (of many) interesting moments.
1. Despite one of the first the stated goals of the hearing (clarify what is AI), no one of the four panelists offered a clear definition, except saying “AI is what we see in the futuristic movies” (meaning, basically, devices acting like people). I would like to have a discussion about my definition of AI (which as an artificially manufacture system which can create solutions to problems the system has never solved before).
2. When asked when AI could exhibit reasoning abilities similar to human, all four panelists offered numbers between 20 and 30 years from now. Which makes a perfect sense to me. If they said "fifty" congressmen could start thinking "well, if it so far ahead, what's the all fuss, we have more pressing matters to finance?". But they just could not say "ten" because they all knew (and all in the field know, and they knew they know) that "ten years from now" is just not realistic, not believable (and lying to the Congress is bad – at least according to movies). 

3. When asked about the areas where AI can bring significant advances, NONE (!) of the participants named education. Clearly “big fish” in AI don’t have education on the list of their priorities (didn’t pop up in their mind), or at least as a potential funding generated field. That is despite the fact that the training procedures they use to “teach” AI, such as “supervised learning” and “reinforcement learning”, are just simplest teaching approaches – way before, say, John Dewey’s Constructivism. The reason behind this fact is very simple – current AI does NOT require any complicated teaching strategy, current AI is not really smarter than a dog (can recognize a face, a voice, a command), well, very fast thinking dog. And since it will not be requiring such a strategy for at least twenty years, why even bother? This is one of the reasons that all my attempts to reach out to AI professionals failed. And this one of the reasons for me to start an open search for collaborators interested into merging advance in AI with education.

For more on AI:

The Dawn of The New AI Era.

Will Artificial Intelligence Save, Replace or even Affect Education Practices? (a venture capitalist’s view)

What does an educator need to know about a brain?

Is Artificial Intelligence Already Actual Intelligence? 

And this link is to the post about how to teach students to make them ready to the AI-era

Thank you for visiting,
Dr. Valentin Voroshilov
Education Advancement Professionals

To learn more about my professional experience:
The voices of my students 
"The Backpack Full of Cahs": pointing at a problem, not offering a solution
Essentials of Teaching Science

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