Why This Result (2025)

When we ask an AI a question, we receive an answer—often eloquent and highly convincing. But why exactly this answer?

Large Language Models (LLMs) cannot explain for themselves which processes lead to a particular output. Even in humans, the genesis of thought remains largely a mystery. We can observe, reflect on, and meditatively examine our thinking—but how a thought arises, which neural pathways are activated, and why these particular pathways fire and not others, remains beyond our comprehension.

The critical difference with artificial intelligence, however, lies in ownership: Humans own themselves. An AI is owned by a company. Its answers are the product of training decisions—what data it knows, which perspectives have been weighted, what it is allowed to say and what it is not.

The question “Why this result?” therefore poses a question of power: Who determines what the machine tells us, what it conceals—and how it might manipulate us?