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

    Editor Times FeaturedBy Editor Times FeaturedAugust 18, 2025No Comments2 Mins Read
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    The randomness inherent in AI textual content technology compounds this downside. Even with equivalent prompts, an AI mannequin would possibly give barely completely different responses about its personal capabilities every time you ask.

    Different layers additionally form AI responses

    Even when a language mannequin someway had good information of its personal workings, different layers of AI chatbot functions could be utterly opaque. For instance, trendy AI assistants like ChatGPT aren’t single fashions however orchestrated systems of a number of AI fashions working collectively, every largely “unaware” of the others’ existence or capabilities. For example, OpenAI makes use of separate moderation layer fashions whose operations are utterly separate from the underlying language fashions producing the bottom textual content.

    While you ask ChatGPT about its capabilities, the language mannequin producing the response has little information of what the moderation layer would possibly block, what instruments could be obtainable within the broader system (except for what OpenAI informed it in a system immediate), or precisely what post-processing will happen. It is like asking one division in an organization concerning the capabilities of one other division with a totally completely different set of inner guidelines.

    Maybe most significantly, customers are all the time directing the AI’s output by way of their prompts, even after they do not understand it. When Lemkin requested Replit whether or not rollbacks had been potential after a database deletion, his involved framing seemingly prompted a response that matched that concern—producing a proof for why restoration could be unimaginable quite than precisely assessing precise system capabilities.

    This creates a suggestions loop the place frightened customers asking “Did you simply destroy all the pieces?” usually tend to obtain responses confirming their fears, not as a result of the AI system has assessed the scenario, however as a result of it is producing textual content that matches the emotional context of the immediate.

    A lifetime of listening to people clarify their actions and thought processes has led us to consider that these sorts of written explanations should have some stage of self-knowledge behind them. That is simply not true with LLMs which are merely mimicking these sorts of textual content patterns to guess at their very own capabilities and flaws.



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