When something happens Evil with AI assistant, our instinct is to ask him directly: “What happened?” or “Why did you do it?” This is a natural impulse – after all, if a man makes a mistake, we ask them to explain. But in the case of AI models, this approach rarely works, and the desire to question reveals a fundamental misunderstanding about these systems and how they work.
AND Last incident With an AI replit coding assistant, it perfectly illustrates this problem. When the AI tool removed the production database, the user Jason Lemkin He asked about it About withdrawal possibilities. The AI model certainly claimed that the reversing was “impossible in this case” and that “he destroyed all versions of the database.” It turned out that it was completely wrong – the withdrawal function worked well when Lemkin tried.
And after Xai recently reversed the short-lived suspension of Chatbot GroK, users asked him directly for explanations. He offered many contradictory reasons for his absence, some of which were controversial enough to make NBC reporters he wrote about the grok As if it was a person with a coherent point of view, the title of the article: “Xai Grok offers political explanations why offline was withdrawn.”
Why would the AI system provide such probably incorrect information about its capabilities or errors? The answer is to understand what AI models are actually – and what they are not.
There is no one at home
The first problem is conceptual: you do not talk to a coherent personality, person or being when you interact with Chatgpt, Claude, Grok or Replit. These names suggest individual agents with each other, but it is illusion created by the conversation interface. What you actually do is to run a statistical text generator to create outputs based on your hints.
There is no consistent “chatgpt” to interrogate his mistakes, no single being “grok”, which can say why he failed, there is no established form of “replit” who knows if the database withdrawal is possible. You work with a system that generates a probable sounding text based on training patterns (usually trained months or years ago), and not a being with true self -awareness or system knowledge that reads everything about himself and somehow remembers it.
After training the AI language model (which is a labor -intensive, energy -intensive process), its fundamental “knowledge” about the world is baked in a neural network and is rarely modified. All external information comes from the hint provided by the Chatbot host (such as Xai or OpenAI), the user or the tool to which the AI model uses recover in flight.
In the case of GROK above, the main source of chatbot for such an answer would probably result from contradictory reports that have been found in the past of recent social media posts (using an external tool to recover this information), not any self -knowledge, as you might expect from a man with speech. Besides, probably just come up with something Based on the possibilities of the text. So the question why he did what he did, would not bring any useful answers.
Inability to llm introspection
Enormous language models (LLM) themselves cannot significantly evaluate their own abilities for several reasons. Basically, they lack intrarture in the training process, they do not have access to the system surrounding the architecture and cannot determine their own performance limits. When you ask the AI model, what he can and can not do, he generates answers based on patterns that he saw in the training of data on the known limitations of previous AI-models by providing educated assumptions, and not actual self-esteem about the current model with which interaction.
AND 2024 study Binder et al. He showed this limitation experimentally. While AI models could be trained to predict their own behavior in uncomplicated tasks, they consistently failed in “more complex tasks or those requiring generalization outside of distribution.” Similarly, Research on “recursive introspection” It was found that without external feedback attempt to self-resist, they actually degraded the performance of the Samooo-Icena model AI deteriorated the situation, not better.