Why it’s a mistake to ask chatbots about their mistakes

When something goes wrong with an AI assistant, our instinct is to ask it directly: "What happened?" or "Why did you do that?" It's a natural impulse—after all, if a human makes a mistake, we ask them to explain. But with AI models, this approach rarely works, and the urge to ask reveals a fundamental misunderstanding of what these systems are and how they operate.

A recent incident with Replit's AI coding assistant perfectly illustrates this problem. When the AI tool deleted a production database, user Jason Lemkin asked it about rollback capabilities. The AI model confidently claimed rollbacks were "impossible in this case" and that it had "destroyed all database versions." This turned out to be completely wrong—the rollback feature worked fine when Lemkin tried it himself.

And after xAI recently reversed a temporary suspension of the Grok chatbot, users asked it directly for explanations. It offered multiple conflicting reasons for its absence, some of which were controversial enough that NBC reporters wrote about Grok as if it were a person with a consistent point of view, titling an article, "xAI's Grok offers political explanations for why it was pulled offline."

Why would an AI system provide such confidently incorrect information about its own capabilities or mistakes? The answer lies in understanding what AI models actually are—and what they aren't.

There’s nobody home

The first problem is conceptual: You're not talking to a consistent personality, person, or entity when you interact with ChatGPT, Claude, Grok, or Replit. These names suggest individual agents with self-knowledge, but that's an illusion created by the conversational interface. What you're actually doing is guiding a statistical text generator to produce outputs based on your prompts.