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.

Philippe Agripnidis