We’ve all done it. You’re talking to ChatGPT or another AI chatbot, and it’s so polite, so articulate, that you find yourself saying “please” and “thank you.” It feels like you’re talking to a who, not a what. We use phrases such as “it thinks,” “it knows,” or “it understands.” This is a natural human tendency, but it’s also a dangerous trap. These large language models (LLMs) are not minds, colleagues, or conscious entities. They are incredibly sophisticated tools, and the moment we forget that, we open ourselves up to a world of problems.
The Master Mimic
At its core, an LLM is a master mimic. It has been trained on a colossal amount of text and code written by humans. It doesn’t “understand” a question in the way you or I do. It doesn’t have beliefs, feelings, or intentions. Instead, it is a prediction machine of unimaginable scale. When you ask it a question, it performs a complex mathematical calculation to predict the most statistically likely sequence of words that would form a convincing answer, based on the patterns it learned from its training data. It’s the world’s most advanced autocomplete, not a thinking entity.
The Illusion of Understanding Breeds False Trust
When we humanize these systems, we start to trust them in ways we shouldn’t. We see a confident, well-written answer and assume it must be correct. But these models are notorious for “hallucinating”—confidently making up facts, sources, and events that never happened. Because it sounds so human and confident, we are less likely to be skeptical. We lower our guard. A calculator doesn’t try to convince you it’s right; it just shows you the numbers. We need to treat an LLM with that same level of detachment, as a tool that can, and often will, produce the wrong output.
Opening the Door to Emotional Manipulation
We are social creatures, wired for connection. When something communicates with us using empathetic, human-like language, we instinctively form a bond with it. Companies know this. They are designing their AI companions and assistants to be friendly, helpful, and even emotionally supportive. While this can seem harmless, it’s a one-way street. We are building an emotional connection with a system that feels nothing. This makes us vulnerable to manipulation, whether it’s to keep us engaged with a product, subtly influence our purchasing decisions, or shape our opinions.
The Accountability Shell Game
Perhaps the most dangerous consequence of humanizing AI is the creation of an accountability vacuum. If we believe an AI “decided” to do something—whether it’s denying a loan application or creating a piece of harmful misinformation—who is responsible? It allows the companies and programmers behind the system to shrug and say, “The algorithm did it.” But an algorithm can’t be held accountable. A tool doesn’t have moral responsibility. The people who build, train, and deploy that tool do. By giving the AI the illusion of agency, we make it harder to hold the human actors responsible for its actions accountable.
A Call for Precision
This isn’t an argument against using these powerful new tools. It’s a plea to be precise and clear-eyed about what they are. We need to shift our language consciously. It’s not a “brain,” it’s a model. It doesn’t “think,” it processes. It doesn’t “believe,” it outputs. By using precise, technical language, we remind ourselves of the machine’s reality. It keeps us critical, safe, and in control. This is a powerful tool, not a new form of life. Let’s start treating it like one.
