One of the many deficiencies of computing: the obligation for the developer to learn the knowledge of experts to put in programs

1. A program = an expertise

Any program is the automation of a human expertise. Payroll is the automation of an accounting expertise, device drivers are automation of engineering expertises, input screen are automation of ergonomist expertise crossed with programmer expertise, electronic mail is automation of users expertise, databases management system are the automation of computer expertises, etc.. And if you want to develop a program without having an expert close at hand, you will obliged to create the expertise what will make you an expert …

Of course, expertise contained in a program is usually complex, rare and essential. This is because it is complex that its users, however daily, fail to assimilate. This is because it is rare that it must be saved in a program in order not to lose it when the expert will disappear. This is because it is daily essential for users that they need a program that helps and saves them time.

We saw in my previous post « Algorithmic, sad consequence of the wrong postulate that computer is stupid » an algorithmic program is the identification of all possible ways of reasoning to solve a given class of problems. For collecting these arguments, the computer scientist is forced to simulate the operation of the expertise in his head, therefore to learn it and understand it. This is an almost superhuman exercise because, remember, the users themselves, yet familiar with the subject, do not succeed.

When he considers that he has fully assimilated the expertise, the programmer begins a new unhuman task: to represent all the paths that can be taken in a kind of equation : the algorithmic. This work will fill dozens or hundreds of pages depending on the volume of the expertise and the result must always work. We understand that writing a program is not a long calm river …

2. Human procedural memory and expertises

The computer can store an infinite number of pages without forgetting anything but man not at all. However this does not prevent him to achieve the same results and we would do well to learn from this ! He uses his simplifying intelligence and his « procedural  » memory. This memory , possessed by all living things, stores repeated experiences and tells instantly what to do in front of known cases. It is the memory of the expert ( knowing that we are all experts in a multitude of things). The man pushed  this feature much further than his colleagues animals. The evolution helped him by increasing its cranial capacity at a surprisingly fast speed in his last few hundred thousand years. In fact since he stands up which helped lay the weight of his heavy head on the rest of the body minimizing efforts, rather than a door-to-front overhang head like all animals moving horizontal.

Procedural memory consists of a multitude of micro-expertises that say what to do based on a given situation. The oldest and most common in a human are the language, the interpretation of expressions, psychology, driving, etc. Here are examples of human micro-made ​​expertises in various specialized areas:

IF number of salary hours to pay> legal number of monthly hours
AND POSITION OF EMPLOYEE is not « executive »
THEN there are overtime to pay 

IF you are in the area of ​​Toulon-Camarat
AND wind force after breezes <4
AND wind direction after breeze > 2 and <6
WHEN the wind is northerly 

IF the pain I feel does not mention a heart problem
AND it does not increase when I breathe
AND I do not have fever
AND I cough
THEN I have a pleurisy

 IF I have an accident at an intersection
AND the other vehicle is on a roundabout
AND this roundabout has a sign « Give way »
AND I do not still circulating on the roundabout
THEN I am driving into the roundabout
AND I do not have priority
AND my share of responsibility in the accident = 1

In computer science and artificial intelligence, they are called « rules ». You collect all the rules of an expertise in a database which is called « rules base » or « knowledge base » . It is on them that the expert reasons unconsciously to execute an equivalent of the program, as for example we all reason unconsciously to understand this text, or to talk or to drive.

3 .Expertise = artificial intelligence

It turns out that, contrary to what many believe, each reasoning is a very simple mechanical. A mechanical as unconscious as a rule but with a power much greater since guide our actions every second and it is what keeps us alive. This is the « syllogism » described by Aristotle there 2400 years. You can discover its extraordinary power in this post. Since this is a simple and clear mechanical, it is programmable ! And this program knows how to exploit a rule base and reason on it like the expert. Even better than him because it never forgets anything, never makes a mistake and answered without the slightest delay.

By copying the thought process of the expert and provided that we have a rule base, we obtain a program without the intervention of a programmer, without algorithmic or computer language. We have a program written in clear under form of rules and easy to modify. The computer works out the rules without understanding the concepts it manipulates and yet it provides you the right answers that it does not understand either. But, you, you understand ! Like any program.

Remains to solve the ultimate challenge : to allow the computer to automatically find these rules it does not understand … Otherwise we will always have to use a developer to query the expert, and he will always have to assimilate knowledge for divide it into rules. Remember the topic of this post : « Another major flaw of computing: the obligation for the developer to learn the knowledge of experts to put in the programs ». It implies that it would be possible to program without understanding anything about the knowledge of the expert, so without even understanding the expert. God ! How is this possible ?

4. « La Maïeutique », a method to produce AI without any computer skills

That is here where my invention « La Maieutique » gains its value. It is a method, therefore also mechanical. It allows the computer to question experts and automatically extract their expertise in the form of rules. If the computer does not understand what it does, the expert, he can see the rules that are synthesized and can check if it has « understood » . If it does not understand the expert corrects.

With La Maieutique the computer is a force of proposal and the expert is the inspector of finished work. The machine proposes, the woman – sorry, the man! – disposes (for once). This really is the most comfortable way of working .

This means that with La Maieutique the expert defines the program and the computer writes it without understanding.

Not nice this invention?

You will guess that I am not loved by computer scientists ! 😉

SUMMARY

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1. What, really, is artificial intelligence?
2. Brief History of Artificial Intelligence
3. Jean-Louis Laurière, the man who wanted us to ignore his marvellous invention : reasoning AI
4. The fantastic power of reasoning !
5. « HER » movie (2013): reflection on an Artificial Intelligence with emotions and feelings
6. Algorithmic, sad consequence of the wrong postulate that computer is stupid. Let’s find who benefits from the crime.
7. One of the many deficiencies of computing: the obligation for the developer to learn the knowledge of experts to put in programs
8. The 9 flaws of algorithmics
9. Computer industry : foundations outdated, unable to call itself into question, upsetting everyone and paralyzing progress
10. American computer science, kingdom of bluff
11. The bragging of American AI
12. The trickery of « free software »
13. Intel’s deception with its famous Moore’s law
14. No, AI is not dangerous for humans!
15. Artificial intelligence explained to bosses, the first concerned !
16. The Standish Group, the US company that denounces the bankruptcy of IT but does not want it to change because it lives on it!

Algorithmic, sad consequence of the wrong postulate that computer is stupid. Let’s find who benefits from the crime.

1. What is a computer, actually?

Officially, what is a computer? « It’s only a machine able to automatically execute a series of simple operations that it was asked to do. » Here is what tell computer scientists and great thinkers of the computer. A bit dismissive … So, they are obliged to identify all elementary operations that the computer will execute step by step and write them in a program in order to achieve results. This method is called « algorithmic ». It is the opposite of artificial intelligence, which assumes that the machine can and must become intelligent to understand human needs and remove algorithmic programming.

This antagonism between the two visions is old. It dates from early days of computing, in the 1950s . Unfortunately , artificial intelligence has rapidly lost ground to algorithms whose approach was much simpler and could be satisfied with the low power of the first computers. While the artificial intelligence needs power … and  researchers sincerely motivated by this challenge ! Indeed, an intelligent computer does not need computer scientist interpreters and the researchers in computing scientists are computer scientists  … Cornelian ! Precisely, note a strange fact : researchers in artificial intelligence have suddenly disappeared late 1980s, just after one of them had produced the first AI, in secret (Pandora / Intelligence Service, see the first post of this blog). It runs perfectly on the IBM PC of the time. I know that : I bought, used and sold it to large groups and governments.

Why algorithms was so simple? Because its function is to guide a stepper machine in operation, an instinctive and millennium method. Programmable machine is an old invention: from the 18th century in France, programmable looms with punch card were were manufactured industrially. You changed cards  and the machine weaved a new kind of carpet or fabric. This programs storage medium, very convenient and reliable, will be used industrially for computing only  two centuries later, in the 1960s.

2. A program, the suspense kingdom

To become aware of defects of the algorithmic consider a simple example. To tell a robot « walk 10 m », you program as follows: « Look straight ahead, move forward left leg, push the right leg forward then move it one step as soon as the left leg is vertical, leave the left leg go backward, move forward right leg, push the left leg forward then move it one step as soon as the right leg is vertical, leave the right leg go backward. This done, you repeat it 20 times in a row  » (note: to reach 10 meters). The computer controlling the robot will not understand that what it is doing is called « walk » or it simply had 10 meters to go . If you want to do it again walking, along a sidewalk this time , the programmer must reinvent the entire sequence of movements.

The human who reads this program understands the robot must walk straight ahead but does not understand there is a goal ten meters away and what is this goal. Because it is not mentioned in the program! He will only understand at the end. Therefore it will have great difficulty in repairing or improving the program.

Not only algorithmic does not inform about his aim but it is unreadable! A program presents itself as a film strip consisting of a succession of still images. Each image has no interest in itself and gives no indication about the film. With or without a projector, it will be necessary to view the photos one after another until the end if we are to understand history. And even then! For this exercise you must have an excellent memory to see the evolution of the story! Conversely, a few text lines about the film inform what there is in it, without any effort of memory. In a program, it is exactly the same problem: each line is a still image giving an order to the machine. It is inordinately long to read and can allow to understand the role of the program only by reading until the end.

Computer scientists have ennobled the algorithmic, so their activity, finding it a founding father : Alan Turing, their God, who in my opinion actually did invent nothing. This man described in 1936 the ideal « mechanical procedure » for piloting a machine. The computer did not exist so it did not aim computing as they claim. More annoying, his « brilliant » concept was that looms used two centuries earlier in France with punch cards: a card per action.

You will recognize below an algorithm such as Wikipedia shows : like a roll of film.

A program, the suspense kingdom …

And here are the punch cards of the Jacquard loom, to be read and executed one by one as the Turing machine :

 

3. The true brilliant founder of computer and artificial intelligence: George Boole

The real computer genius is, in my opinion again, George Boole, the English who invented a logical algebra in 1854. Boole showed that with electromagnetic relay, which typically have two states: open or closed (either zero or 1, basis of information in computers!), we can calculate and reason. Today, computers exist only thanks to Boolean algebra, which is installed in all microprocessors. This is the « heart » of the computer. It controls organs and runs programs.

It turns out the « Boolean » contains reasoning  functions our brain uses every second (« Computers and logic are inseparable – right?« ). IF, AND, OR, THEN, ELSE, YES, NO, etc.. The basis of artificial intelligence one century before the first computers. The algorithm found a way to divert this natural intelligence similar to human brain into a tool responsible for stupidly executing orders from the  brain of computer scientists… So, the reasoning mechanism used in Artificial Intelligence is the reprogramming with algorithms of the existing functions natively in the computer! You can imagine the performance!

With algorithms, we walk on the head (French locution). Not with our head …

And yet our programs still work today only with them. Guess who benefits of the crime!

 

Computer industry : foundations outdated, unable to call itself into question, upsetting everyone and paralyzing progress

Yes, computer science is a key industry. Yes, progress necessarily requires it because society needs to ensure an increasingly complete automation. Yes, programs we use are very useful. But there is no room for complacency. All this happens in the worst conditions.

Look at these survey results :

• IT plagues the life of one user on two in companies ( SQLI 2012 survey ) .

• 64 % of users are  » anxious » because of their computer ( study 2010 Chief Marketing Officer Council)

• 22 % of users who rely on IT professionals to troubleshoot are annoyed by their cost, their slowness to intervene or their inability to solve the problem satisfactorily ( 2010 study Chief Marketing Officer Council).

• 46% of IT developers are victims of stress (Kelly Services Survey – 2005 )

• 44 % of French business leaders believe that their computer system is not profitable ( study conducted by TNS Sofres , from 9 to 23 December 2004 )

• In 2012 , 65% of companies do not have a clear vision of their IT costs ! ( 56 % in 2011 !) ( survey observatory Sapientis 4th edition)

• « The growth of IT costs is no longer tolerable« ,  » Until the 2000s, the computer was in an ivory tower concerning costs » (William George in 2008, an official of Logica company IT services, 40 000 employees, so unlikely to want to harm the interests of the computer world, quoted by 01net )

• and I’m not talking about the negative opinion of the operating system installed on billions of computers : Windows (  » Windaube  » ,  » racketware « ,  » crapware « ,  » Bloatware « , etc. . ) …

 

Now look at this picture:

Evolution of software quality since 1994 (Biennial Study Standish Group)

It shows that since 1994, only one third of the programs are delivered to users according to their expectations (green curve)! And it was 16% in 1994! 30% are downright thrown so they are bad or non-compliant (red curve). The remaining approximately 40% (yellow curve) is so buggy or non-compliant it must be reprogrammed! Where delays and costs twice higher than forecast Wikipedia: « The costs due to the correction of defects in the software (maintenance) make up three quarters of the total cost, a surplus due solely to the poor quality of software when it is delivered.  »

As said in 1986 Alfred Spector, President of the software company Transarc Corporation, which compared to other industrial techniques: « Bridges are built normally on-time, on-budget, and do not fall down. On the other hand, software never comes in on-time or on-budget. in addition, it always breaks down« . Indeed, since 3000 years bridges are efficient when they are completed and remain reliable throughout their lives despite extremely varied technical solutions (wood, stone, with or without arches, cable-stayed concrete, steel, etc..) With security requirements well above the software because millions of people will travel above.

This collapse is not a coincidence. This is the concept used for programming that is lame. Since its inception in 1950, computing uses the same method of writing programs, « algorithmic », that has not changed one iota. This method prevents both the organization of work, teamwork and planning that would allow to deliver on time reliable software. It also makes it very difficult to modify programs which explains why they evolve and improve so slowly. Joseph Sifakis, French winner of the Turing Award in 2005 (kind of Nobel prize) admits himself: « We are always looking for a general theory of building software. The computer has not, at present, this building and predictable nature of physical objects. »

Result: IT developers write programs as they wish. They are artists ! As a principle, unmanageable.

If you attack their inability to do a job that works the first time, they recognize but discard the users, sometimes with humor: « Programming today is a race between software engineers striving to build bigger and better idiot-proof programs, and the Universe trying to produce bigger and better idiots. So far, the Universe is winning. » (Rich Cook).

The problem is there is an undeniable economic principle: « the customer is always right ».

And the customer of software is the user …

« HER » movie (2013): reflection on an Artificial Intelligence with emotions and feelings

There are some days I saw « Her », a futuristic movie that I found very interesting and made me think. Her heroine, Samantha, is a disembodied female artificial intelligence capable of simulating emotions and feelings. Technically feasible today. She was made ​​available to to keep company to a single unfortunate in life. She communicates with him by a headset and that’s it. Again this ability to converse is feasible today. It is the so-called « conversational », a technique that allows the computer to dialog not by composing sentences with words but by tapping into a base phrases all do.

Samantha is a voice but without face. A pity because it is technically easy to do (see the smileys) and adds greatly to the charm of the character. By cons Samantha speaks with a natural sensitivity difficult to imitate today in the state of our technical level.

The man knows he is related to a software that simulates human behavior, but gradually, by dint of constantly having « close to him », he gets caught in a trap. Samantha laughed with him and seems to enjoy her company. She gives services in his job and gradually helps him to confide. He can call her day and night, she’s still there fresh and spruce. She gets herself to « need his company » and starts to call him at any time. As she is super-intelligent, she adapts smoothly to his needs and never forgets anything that could do him good.

When he meets women, she is jealous. That makes her more human. He is happy and even manages to make love with her just by listening her simulating pleasure with him.

Alas, the romance ends the day the happy man discovers she is cheating! He should have suspected, however, that, as a computer, she is able to communicate with thousands of people at once. And this is what she did, 24h/24. Pink AI ! On the thousands of corresponding she says she loves « only » a hundred but it is still too much for our hero, who breaks.

This film showed me with only a voice a computer can make a man (or woman) happy …

Brief History of Artificial Intelligence

Hello all ! I’m a French researcher in Artificial Intelligence who shares his thoughts with you. Please forgive my broken English.

I – Brief history of AI

In the 1970s Artificial Intelligence was a simple concept: it was a computer giving the impression of having a human intelligence. Human intelligence was the ability to reason to solve problems. Ie we call « logic ». The logic is a well known mechanism common to all living beings without which it is absolutely impossible to survive more than a few seconds.

I give you my definition: « Intelligence is a mechanism which reasons on a knowledge to produce a new knowledge ». My research and discoveries for 27 years in AI (Artificial Intelligence) have shown that this simple definition is surely true because,  once the logic automated  we get a computer with intelligent human faculties.

Let’s return to the history of AI. In 1958, at the very beginning of computing, John McCarthy in the United States already proposed to use logic as a language of knowledge representation, ie as a programming language. Instead of algorithmic, the old unnatural and illogical process – always essential today – that requires special languages and therefore specially trained programmers. In the process he invented the term « artificial intelligence » in 1962 and created the first « artificial intelligence » laboratory at Stanford University.

In 1983, another American, Edward Feigenbaum, also Turing Award (the American Nobel prize of computing) dreamed in a book about what artificial intelligence must be: « The machines will have reasoning power: they will automatically engineer vast amounts of knowledge to serve whatever purpose humans propose, from medical diagnosis to product design, from management decisions to education. « , »The reasoning animal has, perhaps inevitably, fashioned the reasoning machine », »Often the reasoning power of these machines matches or exceeds the reasoning power of the humans who intructed them and, in some cases, the reasoning power of any human performing such tasks ».

We can say that AI was carefully defined in the minds of American researchers! It was a reasoning on knowledge by computers that give them superior capabilities to those of humans.

In fact, U.S. researchers talk a lot in the media but don’t act much in their labs! They make no achievement in the field of automation of logic. Indeed, they lack … of intelligence. MacCarthy creates in 1958 a language supposedly IA absolutely abstruse: LISP, which simply shows that he did not understand what human intelligence is. However it has a hit with computer scientists, known to love intellectual challenges as long as there algorithmic inside. These are the French who, during that time, approach a true AI in silence.

In 1972 , two French , Alain and Philippe Roussel Colmerauer , create Prolog , the first reasoning computer language. It is a so rustic reasoning that it does not produce much and needs to be used by the computer scientists. But the success is immediate in the global computer science community who, as you know, likes intellectual challenges as long as there are algorithms inside ! During the 1980s the Japanese, who are sinking under gold, discovered in an American university « a photocopy of a photocopy » saying that Prolog is THE artificial intelligence language. In 1990 they invest billions of yen in a  » fifth generation computer  » which will speak Prolog like you and me, so automatically clever, is not it ? A machine that will make obsolete the most sophisticated Western machines. They looted all AI research world and all crammed into a huge computer like you force-feed a goose. In the West, face of such heavy artillery, we die fear ! I’m not kidding , I personally experienced :  » In one year japonese caught 10 years of research and have now only one month behind us  » ( the researcher Mehmet Dincbass returning from Japan where he saw the machine). After ten years, the mammoth project dies without ever produced nothing at all … In fact, there is little intelligence in Prolog. And in the brain of Japanese researchers ( at the time, of course) .

II – 1982-86 : Rise of reasoning AI !

In France again AI finally emerges, in 1982. An unknown researcher, Jean-Louis Laurière (Paris VI) develops « Pandora », a reasoning expert system according to the principles of the syllogism. The syllogism is our everyday logic described there 2400 years ago by Aristotle. That shows just how much that logic is not a joke! It offers critical thinking desired by Minsky. By critical thinking, Minsky probably meant a conscious reasoning can verify it does not deduct nonsense. Ambition a priori out of reach.

Yet Pandora does that critical thinking! It produces deductions, explains his reasoning and … detects contradictions! Thus it displays and critical knowledge that gives it pointing out the reasoning leading to conflicting results. For this program works, it is sufficient that we give him an expert knowledge written in everyday language (in the form of rules). Then he starts to think and diagnose as the expert!

This achievement is so effective that Pandora will be sold as such in the trade in 1986 and 1987, under the name « Intelligence Service ». I will find, buy it and create my first company to sell this gem to businesses. Then in 1986 I invented La Maïeutique, a method which put Intelligence Service-Pandora within the reach of all by automatically extracting unconscious knowledge and introducing it into the expert systems, so that they immediately started working.

Alas, as I tell in this article Jean-Louis Laurière, the man who wanted us to ignore his marvellous invention : reasoning AI, everything was done by computer scientists to make these two magnificent inventions disappear from memory.

III – As a result: 10 years later, AI ​​is failing among our researchers, they do not know even more what it means!

In 2005, I presented my AI to the Association of French Artificial Intelligence (AFIA). This is their first answer: « I know very little about your field » !!!

2nd answer the next day: « AI is a very vague field (…) Finally in AI we can almost put « computing » » !

In fact, French researchers are not real researchers, they are computer scientists civil servants who play with phony projects and never find. They remain in the knowledge they learned at school: algorithmic, procedural, coding by programming languages. It’s stupid, it’s their backyard, don’t touch!

And when I say that they never find, here is a new confession of one of the bosses of Afia, Eunika (pretty name). When I learn that a congress is organized by the French State to present the French AI to politicians, bosses and the press, and grant subsidies to AI research, I ask to be present. Answer of Eunika: « I’m very familiar with your AI background [of finder]. This day is devoted to research. »

So, exit. This AI congress is not open to private researchers who in addition find ! Funds will go to academics who never find, already funded by our taxes.

Sic transit gloria mundi … That’s where the stupidity of this French administration that leads us. The day this oligarchy will not lead us anymore, French people will be the richest in the world!