Dangerous Narrative AI

 The dominant discourse around AIG, particularly LLMs, is tainted by a dangerous narrative, which is the misattribution of human capabilities such as “reasoning,” “thinking,” and “interpretability” to systems that, in essence, operate in radically different ways. The article below, in a lucid analysis, based on strong evidence, demonstrates that this tendency is misguided.

A closer understanding of the inner workings of these models reveals that the so-called “intermediate tokens,” the steps in information processing, are not manifestations of thought or reasoning. They are better explained by complex mathematical and statistical structures, visualized in elegant graphs, but fundamentally non-anthropomorphic. What is observed is, in reality, a process of prompt augmentation, highly dependent on formal checkers. These checkers are external mechanisms that guide and validate the process within specific and limited settings, not an intrinsic capability of the model.

The term “interpretability” has acquired a worrisome status. When applied to the analysis of these intermediate tokens without a robust causal basis and real verifiability, it is nothing more than an attempt to extract meaning from what is merely a complex statistical correlation. Just as the protrusions on a person’s skull do not reveal a person’s future or health status, the “interpretation” of an AI model’s internal signals lacks scientific foundation.

The anthropomorphization of terms like reasoning and interpretability is, in fact, a misappropriation of language to lend illusory credibility, attract investment, or mask technical limitations. And when adopted by consumers and enthusiasts, this same anthropomorphization often reflects a lack of access to technical criticism. It is an understandable mistake, but no less damaging for perpetuating myths.

The tendency to anthropomorphize sophisticated statistical systems is not benign. It obscures the true nature of the technology, opens the door to excessive hype, and diverts resources and attention from AI research beyond AIG. Recognizing that prompt augmentation guided by formal verifiers is at the core of current operation, and not a simulacrum of thought, is essential for sound and ethical AI development. The future of AI depends on the ability to distinguish between mathematical elegance and the illusion of consciousness.

* AIG - Artificial Inteligence Generative