AI Limits, Dangers and Threats: A tool without Mastery

Par Philippe Agripnidis

If you want to understand, without any technical jargon, what the limits, dangers, threats and conceptual flaws of artificial intelligence are, then this book is fully suited to your desire for knowledge and understanding.

You'll discover that AI, which wants to present itself as an exceptional computing advance, is in fact more than 10 years behind the technologies already available. And what's more, AI designers don't know how to explain the whys and wherefores of the information their software provides when used. They don't know what goes on in the computer mill of their own codes. AI is like a parrot armed with a photocopier enclosed in a watertight black box. It only reproduces what it has seen or heard before being captured. It's not a question of providing the relevant or the appropriate, or even the true or the certain, but the credible, the probable, the possible.

You will also learn that, although presented as a marvel of automatism, AI only functions through perpetual human corrections. And that, despite this, there have been many instances of behavioral slippage. And that more will follow. For it is the very nature of this so-called artificial intelligence to be subject to its own contradictions and errors. You'll also see how AIs become bipolar, oscillating between phases of information bulimia and purging of superfluous data.

You'll also get an insight into why, despite its limitations, AI fascinates us. And why we use it. And the first economic, social, psychological and cognitive backlashes that are beginning to appear.

The book also presents the fundamental threats inherent in AI. They are intrinsic to the approach that presided over its conception. If we can calculate everything, on every subject and all the time, then let's calculate everything. But without going into the depths, without any real knowledge of the World. By keeping the approach of flat thinking, to a single time of reflection. Because AI's greatest weakness is that it is built on a limiting and confusing tool: text. To create new Knowledge, AI is like a propeller engine that wants to go to the Moon. As soon as it reaches a certain threshold, it is no longer efficient. There's a glass ceiling that AI will never be able to break through to bring us the necessary evolution or progress that Humanity needs at the start of the 21st century.

It should be noted that this book is the third part of another: "Prelude to Quantum Graphs", with a few additions, updates and simplifications. For the original part was written in deep and recurrent connection with the notion of Quantum Graphs, which goes beyond the simple problem of AI. It was timely to present these insights without this entanglement with Quantum Graphs, which are the antidote and alternative to AI through the universal construction of standardized, structured and articulated knowledge models.

• Langue: Français
• Éditeur: Publishdrive
• Date de sortie: 20 nov. 2023
• ISBN: 9782487087095

Aperçu du livre

FOREWORD

Global intellectual property rights

Under article L.122-5, 2° and 3° a) of the French Intellectual Property Code, only copies or reproductions strictly reserved for the private use of the copier and not intended for collective use and only analyses and short quotations for the purposes of examples and illustration are authorized, and any representation or reproduction, in whole or in part, made without the consent of the author or his successors in title or assigns is unlawful (art. L. 122-4). Such representation or reproduction, by any means whatsoever, would therefore constitute an infringement punishable under articles L 335-2 et seq. of the French Intellectual Property Code.

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No smileys but ironic dots ¡

Rather than using the punctuation marks used on digital media, such as :-) and ;-), we’ve opted for the inverted exclamation mark ¡, which is an aesthetically and typographically pleasing replacement for these two encodings. One ¡ is equivalent to :-) and three ¡ to ;-). Thus ¡¡¡.

Use of Wikipedia

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STAKES AND FUNCTIONS

Artificial intelligence stakes and contexts

A disproportionate and growing importance

Hardly a day, or even an hour, goes by without news about Artificial Intelligence (AI) appearing in the newspapers or on our news feeds. Adorned with all manner of virtues, it seems to be a magic formula, a digital philosopher’s stone capable of curing all of humanity’s ills. Its invocation could lift mountains and move oceans. Effortlessly. And without a backlash. All our worries, all our problems will be solved, by a few clever calculations from thousands of interlinked processors that will scientifically and truthfully—how could it be otherwise—bring us the best solutions at the lowest cost. This is indeed the promise of AI.

But where there’s promise, there’s hope. But not guarantees and certainty. This is one of the first ambiguities of AI. It is not the least. But the most serious problems stem from the dispossession of human beings of their ability, duty and obligation to think for themselves.

Fortunately, if the danger is real, there is at least one alternative to mitigate these potentially catastrophic drifts. It’s based on the notion of Knowledge Models and Quantum Graphs. The latter are presented in the book (in French) Prélude aux Graphes Quantiques, available on digital distribution platforms and in hard copy on Amazon. The information you are about to read about artificial intelligence in the present work is taken from this first book, which includes, in addition to a development on the antidote and alternative to AI, a presentation of the Quantum Graphs method. The formalization of standardized, structured and articulated Information that it enables leads to the generation of Knowledge Models. It’s this method and convention that we’ll be referring to when we speak of Knowledge Models.

The chapters to come will be devoted to describing how AI works, presenting its dangers, its limits, its threats. And its cardinal flaw, the use of text. Which means that, instead of being the rocket engine it would like to be, it’s just a beautiful propeller engine that won’t take us to the heights of human civilization.

So, let’s start with a few basics about AI, before looking at how it works.

A few basics

This is not intended to be a technical course on artificial intelligence. There are many relevant books on the subject, as well as free videos and training courses on the Internet.

Because more than just the appearance of computers, we’re going to develop the very principle of artificial intelligence. What it is essentially based on. Its vision of the world. Or at least those of its designers. And we’ll see what this implies in terms of limitations and illusions.

About time! From black-and-white into the land of color

As a stumbling block to your thinking about what AI is, what it really brings, in terms of opportunities or threats, you need to integrate the following information. What artificial intelligence will achieve by the end of 2023 is absolutely normal. There are no spectacular achievements to celebrate. There’s nothing to be astonished about. The only reason to marvel would be that this is happening so late in the history of computing! After all, everything had been ready since 2010: server farms, powerful processors, high-capacity hard disks, abundant memory, algorithms and, above all, the Internet mesh to suck in data and disseminate it, so that AI in 2023 mode would already exist. It’s just, finally, the computer’s ability to create content that’s being used. For text and images. There’s nothing magical or surprising about it. It would be like being surprised to see black-and-white images on a color television. Because IT can generate much more than AI.

It’s the delay in getting to this level that should make us wonder. Given that all this is based on old methods and forms of data storage and statistical exploitation that are in fact obsolete for creating new Knowledge and sharing it. It’s a logical outcome. But of an older generation. It’s a limitation and an end. We won’t go any further collectively with this tool. So, there’s no adoration to be had for current AI. That’s why this book has been written. To raise awareness—to inform—to alert. And to help spread a fair vision of AI’s real capabilities, but also of its limits and the pitfalls it may contain. And these last two categories are well fulfilled.

A caricatured definition?

If we wanted to express, without any technical concepts or jargon, what generative artificial intelligence viscerally is, we could say that it is: "a parrot in a black box equipped with a photocopier that regularly jams paper". You’ll see that this definition goes much deeper than it might at first appear, in terms of what artificial intelligence intrinsically is. For as long as artificial intelligence is organized the way it is in 2023, it will only repeat and distort what it has collected. And we’ll see in the next section that the designers don’t really know why or how it works. We don’t know, in essence, why there is this result.

The parrot doesn’t know what it’s saying or why it’s saying it. The proof is that if you ask him the same question again, you’ll never get the same answer. What is presented as a strength by the lauders of artificial intelligence is actually a demonstration of its weakness. It is absolutely unable of explaining its choices. And to demonstrate them. It’s like this. You’ll never know why. But don’t worry, neither will he…

What’s more, it’s a parrot that requires you to speak just one foreign language. Since the pioneers in the commercialization of artificial intelligence, OpenAI, were American, the development of the tools was mainly based on this language. Even if, supposedly, AI can also work in other languages such as French, Spanish or Italian. But you don’t get the same efficiency or quantity of output as with the AI’s native language, English. If you’re English or American, you might not mind if the AI speaks Anglo-American. But in fact, it doesn’t really speak that language. And that’s the problem. You have to master another language, the obscure one of the prompt! We’ll go into more detail later, but the prompt is a structuring of commands, of orders that are sent to the artificial intelligence. It’s like telling a dog what to do. But you have to make yourself understood. We’ll come back to this point in the section on the limits of artificial intelligence.

After this initial, non-technical approach, which corresponds well to what artificial intelligence is conceptually speaking, we’re going to move on to a presentation of its technical functioning.

How Artificial Intelligence works

Pulsions and history

Without going into too much detail, there have been several waves of development over the decades. We could trace this idea back to the invention in 1834 by Charles BABBAGE of the first computer concept and the realization of a machine capable of sequentially reading instructions from Jacquard card