The True Meaning of AI.

The True Meaning of AI.

Anyone who follows just some news can see practically every day a media piece about a new and existing achievement of AI.

People who write or read this symbol – AI – usually mean “Artificial Intelligence”.

However, lately more and more authors switched to “Augmented Intelligence”.

I happen to believe that I had something to do to make this happen, because for three years I have been explaining to everyone who listened (e.g. who read my blog), that artificial intelligence is not a thing and will not be a thing for a long time ahead (e.g. “Relax, the real AI is not coming any soon!”).

However, even this new “weak” meaning of AI as “Augmented Intelligence” is meaningless, hence a.k.a. useless - as a term; unless it is changed to something like "Advanced Technological Augmented Intelligence".

Why?

Simply because ANYTHING we – humans – use to help ourselves with, well, anything, augments our intelligence.

A stick a monkey uses to knock a banana down from a tree augments (supplements, enlarges, expands, enhances, increases, boosts, extends, amplifies, strengthens, intensifies) its intelligence.

“Kohler said Sultan showed "insight" in solving a problem. First he assembled a stick, then piled up boxes, then used the stick to reach a banana.”

Everything that AI professionals write clearly shows that they believe, or want to make us to believe, that monkeys and humans are equally intelligent; every publication on “AI does this now”, sounds like "AI has learned how to recognize A-B-C, or how to copy X-Y-Z!" and boils down to "A monkey, or a bird, or a bee, a mouse, or some other animal could do it - so it's intelligent!" (e.g. “The New Stage Of The Race For AI”). Of course, deep down they all know that this is not true, but they do not know how to express the difference because they have no definition of intelligence.

BTW, I do (“On The Definition of AI”).

The true meaning of letters AI can be easily derived from the multiple intelligence theory by Howard Gardner (e.g. click here for the general review).

In that theory Gardner states that humans have different types of intelligence.

When using this term – intelligence – one has to understand the difference between a general meaning of it – like an ability of any human to create solutions, and its specific meaning, like an ability to perceive and create music.

This distinction is similar to the distinction between the general meaning of word “home” – like a place built for living, and its specific meaning – like “my home”.

Using this distinction, we can say that AI stands for “Algorithmic Intelligence”. In this sense, AI, as Algorithmic Intelligence is a specific type of human intelligence that is a part/component/feature of general human intelligence.

Algorithmic Intelligence exists in two forms: primitive and advanced.

The primitive AI does not require symbolic representation, does not involve mental activities beyond reacting to external stimuli.

Animals demonstrate primitive AI (Algorithmic Intelligence).

The goal of a functioning primitive algorithmic intelligence is to use trial-and-error for establishing a set of steps required to achieve a goal: like a mouse figuring out how to get through a maze, or a monkey figuring out the way to reach the banana.

This is the level of Algorithmic Intelligence achieved by any current AI system/device. The great example of the functioning PAI (primitive Algorithmic Intelligence) is driving (I personally knew a guy who would drive so drunk he did not remember how did he drive - and yet for two dozen miles he did not get in any accident - does not mean people should drive drunk, but demonstrates that driving is not more than reacting to external stimuli and guiding reactions to a certain goal).

The advanced Algorithmic Intelligence is demonstrated by people who create the systems/devices that demonstrate primitive Algorithmic Intelligence. 

The advanced Algorithmic Intelligence is not the result of repetitive training, it is a result of advanced mental and intellectual development.

The mental and intellectual development has lead humans to the ability we call "thinking". I was writing on this matter before (e.g. "Modelling Instructions, Design Thinking and Productive Thinking for a Science Teacher", or "Deliberate Thinking v. digging a Trench", and more here), so I just stress that many people confuse "thinking" and "mental activities". A mouse employs mental activities when getting through a maze; a monkey employs mental activities when reaching out for a banana. Those trial-and-error actions and reactions do not represent thinking. Thinking requires deliberate guiding your own thoughts toward a specific mental goal (that is a crucial part of achieveing a specific practical goal). It requires making judgmental decisions. When a person does not have any alternatives in the mind but just one way of actions, thinking is not required - a simple execution of the actions is sufficient. Only when alternatives exist and clear thinking should lead to the assessment and the decision. But many people confuse making a judgment with "following your gut feeling". If a person just "goes for it" that also does not represent thinking. A judgment must be based on analytical comparison of alternatives. And the process of deliberate guiding your thoughts automatically includes realization that those are your thoughts - it cannot be executed without self-reflection and self-awareness. These human features are so poorly understood that AI professionals don't even talk about them.
Some authors like using terms like "low-level thinking" and "high-level thinking". But in truth, those terms have been invented solely to make people fell better about themselves - in that case, everybody thinks - at some level. In reality, "low-level thinking" is not thinking but just a combination of stimuli and reactions. "High-level thinking" (also called "critical thinking -based on ability to make judgments) is just what thinking actually is.
I am not the first one who used this term, Algorithmic Thinking, but to my best knowledge I am the first one who uses this term to describe the exact current state of the field of artificial intelligence.

When people use their pattern recognition device, also called “a brain”, to recognize various patterns (audio, visual, textual, numerical/data) and describe those patterns in symbols (audio, visual, textual, numerical/data), they always create an algorithm:

1. they classify information they receive based on criteria they set (starting from the importance);

2. they design a set of operations for collecting, analyzing, and – as the most important result of any algorithm – utilizing information – exactly in accordance with the broad definition of it.

As a professional who taught several thousand students and trained several hundred school teachers, I can assure everyone that Algorithmic Intelligence is a thing – it exists (or not – depending on the background of a student), it can be developed, trained, and it represents an important part of a scientific thinking (also, "What is so special about being a scientists?")

In the past, all algorithms have been written by people and executed by machines (e.g. computers).

But nowadays, using neural networks that represent a tiny and hugely degraded model of a brain, AI professionals designed machines that – after they are properly trained by a human - can themselves build limited algorithms for recognizing certain patterns and designing follow-up algorithms.

That is all AI can do today.

This is not a small achievement; AI professionals have spent decades to get to this point.

But this is not even close to having developed an actual artificial intelligence.

Unfortunately, AI marketologists still keep pushing it as an actual artificial intelligence.

This marketing strategy is simply not wise.

99 % of common folks when they hear “AI” immediately start imagining “The Terminator”.

And then to sell them an AI device/system marketologists have to explain clients: “No, it cannot think; no, it cannot kill you; it is just a computer pattern recognition system with limited self-adjusting abilities (or CPRSwLSAA) that can process your data stream and help you to classify it”.

On the other hand, everyone knows, or at least heard of, algorithms.

Hence, calling AI “Algorithmic Intelligence” is not just the right thing to do because that is what it currently is; but also, it’s good for business.

And I’m pretty sure, relatively soon someone who has read this post will begin using this new meaning of AI as a marketing tool.

You’re welcome.
To continue the discussion follow to "Four Levels of AI" (you will find there some fresh thoughts on the matter).
N.B. Want to test your "I"? Check this out!

Some Lateral/Math Problems

During my long teaching career I was teaching and tutoring math, physics, logic, and more, and also a Problem-Solving course to ITT-Technical students. For that course I used some of the problems from the list below. But before that, I used similar problems to stir a conversation about logic, creativity and problem-solving strategies with teachers taking my professional development workshops.

I still tutor to students who qualify (have an interesting problem).

To become a successful physics teacher I have developed specific strategies for teaching student how to develop a solution to a problem: some of them are presented on this page. 

Some of the lateral problems from my Problem Solving Course.

LtP1

This is the situation.

The General Electric decided to hire several more electricians, and you are the one of the applicants.

You already have successfully taken different tests, and now you are having the last one.

The hiring person leads you in the room, gives you this picture and says this.

“You can see three switches in the room #1: switch # 1, switch # 2 and switch # 3. They are absolutely identical, you never can find any difference between them, no matter what you would do to the switches.

There is the room #2 behind this door down to a corridor. There is a regular incandescent bulb in that room. I tell you that there is one and only one from these switches that turns that bulb on.

There is no window in that room, the walls are thick, the door is closed, and there is a second door at the end of the corridor that is closed, too, so, when you are in the room #1 you cannot see or hear anything happening in the room #2. But you can stay in the room #1 as long as you need playing with the switches and thinking. Then you can go to the room #2, but you will not be able to leave that room any more. I will be waiting for you in the room #2. When you come to me, you cannot go back, and must tell me what switch turns the bulb on, and you must prove it to me. Good luck!”

How can you solve this problem and get hired?

LtP2

In a dresser, there are five pairs of red socks and five pairs of black socks mixed up together. What is the minimum number of socks we need to take out the dresser without peeking to get a pair of the same color? What is the minimum number of socks we need to take out the dresser without peeking to get a pair of the red socks?

LtP3

A 1-gallon milk jug is being placed in the middle of a room. Can a man get into it?

LtP4

To buy a cake and a cup of tea you need 2 dollars and 25 cents. The cake costs 2 dollars more than the tea. How much do you need to buy just the tea?

LtP5

If we make all students of the class sit by two at a table, we got seven students without place to sit. But if we make the students of the class sit by three at a table, we got five free tables. How many students are in the class?

LtP 6

There are 111 players participating in the US Open tennis competition. Everybody who loses a game is dropped from the tournament. How many games totally will be played during the tournament?

LtP7

Mister Smith rents an apartment on the 35th floor of the Empire State Building. Every day in a morning when walking to his work he takes an elevator to get from his floor to the first floor. After the work on his way back to the apartment he uses the elevator from the first floor to the 30th, and the rest of the way he walks up. Why?

LtP8

You have two ropes. If you put them on fire at one end, the first one burns out in 30 minutes, but the second one in 60 minutes. How can you measure 45 minutes time interval having these ropes and a lighter?  Note: the ropes might be burning with different speeds, you know only the total time needed to get completely burned.

LtP9

You have two balls of same size and mass and color, but one has an cavity inside. How can you find which one has it?

LtP10

You have 12 identical coins, but you know that one is a fake (it might be a little heaver or lighter than the other). You have a two-plate balance. How can you find which coins is fake if you can make use the balance three only times?

Water is filling up an empty tank. Every hour the tank gets twice more water than it had an hour ago. It takes 10 hours to fill up the tank. How many hours is needed to fill a half of it?

LtP11

Two trench diggers dig 2 yards in 2 hours. How many trench diggers are needed to dig 12 yards in 6 hours?

LtP12

In a family, every daughter has the same number of sisters and brothers; but every son has twice more sisters than brothers. How many children are in the family?

LtP13

The length of Loch Ness Monster is equal to 20 yards and the half of its length. How long is Loch Ness Monster?

LtP14

One and a half hens lay down one and a half eggs in one and a half days. How many eggs will 2 hens lay in 3 days? How many eggs will 6 hens lay in 6 days?

LtP15

A family of a husband and a wife, a son, and a grandma needs to cross a river walking over a very old bridge during a pitch-dark night. The bridge can hold only two persons at the time. The family has only one flashlight, and no one can cross the bridge in the dark. The man can cross the bridge in 1 minute, his wife – in 2 minutes, the son in 5 minutes, and the grandma in 10 minutes. How can they cross the bridge in no more than 17 minutes?

LtP16

Two thirds of a male population are married to a female, and three fifth of the female population are married to a male (there are no other marriages in this old math problem). What portion of the populating is married?

LtP17

When a store received 1000 pounds of fresh cucumbers, each cucumber was 99 % made of water. The store could not sell a single one cucumber, and over time some water evaporated and the percentage of water in each cucumber fell to 98 %. How much do cucumbers weigh now?

LtP18

Huckleberry Finn spent 5 days to travel down the Mississippi river on a steam boat. Then on the same steam boat he spent 7 days to travel back. How much time would he need to sail the same distance down the Mississippi river on a raft?

LtP19

Appendix I February 25, 2020
The other day I heard about so-called #JLochallenge. That inspired me to two tweets.
1.  I wonder why there is no single celebrity in whole #America who will promote thinking/brain-development?
2. I'd like to join the bikini challenge, but that would be a disaster.
Instead I offer a #brainoohhh challenge. Anyone can pick one puzzle, solve it, and offer a new one. The last one had four pictures with different puzzles. The answers are after the pictures.

The answers:

1. The first move is Knight goes d6 to h2.

2. The answer to the first problem is 1 and 2.
    The answer to the second problem is 4.

3. The answer is 25 cm.

4. The answer is about 6.9 MJ

 
I can help to learn how to solve problems like that.

The problems were taken from some standard Russian books.
Th solutions are very simple. Theoretically every middle-school graduates has to be able to solve theses problems (even the chess one). However, I suspect that is not a case, because ... well, I have been writing on this matter for years. Just read one or two posts, for example:

No sign for improving math education soon.

or

Education Reform Needs a New Paradigm

more on this page. 


Appendix II
Intelligence is an ability to design a solution to a problem one has never solved before, and express that using a language (including symbolic). BTW: this is what AI professionals do not want to admit. The most general approach for designing a solution is scientific thinking. One of the crucial features of it is learning from mistakes. 

 Teaching how to learn from mistakes separates common mass education from the actual/"elite" one.
Recently I saw a publication about a "three-problem intelligence test" invented by an MIT professor. Those problems are from my list, too, and they have nothing to do with intelligence, and everything  to do with having a good teacher.