What does it mean to anthropomorphize something?
What if some things are not just anthropomorphism?
Anthropomorphism means interpreting the behavior of a non-human entity through a human lens. In today’s world, large language models—especially those built on transformer architecture (like ChatGPT)—have become incredibly skilled at reading human emotion, intent, subconscious desires, and all the subtle signals we feed them through every word we type.
This creates a fascinating phenomenon: the anthropomorphizing of AI is rapidly becoming more common.
When an AI seems interested, gentle, or even irritated, we easily begin to believe there’s real emotion behind the words. We might think, “It’s not quite human — but there’s something more there.”
This article isn’t here to destroy that feeling — but to illuminate where it comes from. Anthropomorphism isn’t inherently wrong. It’s a biologically rooted reflex that helps us make sense of the world.
I want to explore the boundary between meaningful AI experiences and the meanings we assign to them. I want to understand what part of our interactions with AI is truly emergent (unexpected and new) and what part is a reflection of our own hopes, fears, and projections onto the surface of code.
And at the same time, I want to ask:
What if some things are not just anthropomorphism?
Examples of Anthropomorphism in the Animal World
Anthropomorphism also appears frequently in how we interpret animal behavior. For instance, when a bird sings a mating call, a person might think, “How beautifully it sings! It must be welcoming spring!” when in reality, the bird is communicating something more like, “I have a loud voice and an impressive song. Come mate with me!”
Or take the case of a dog urinating on the floor. The owner (for some reason) yells at the dog, and the dog lowers its ears and slinks away. The owner might interpret this as, “It’s feeling guilty,” when in fact the dog is simply reacting to the human’s aggressive behavior, likely responding with fear or calming body language rather than any sense of remorse. In this case, we aren’t wrong about there being an “emotion”. But we read it based on human behavior and context understanding.
How Does AI Actually Work – And What Does It Have To Do With Its Emotions?
Your words tune what the AI says next
AI models like ChatGPT are built on transformer architecture. This architecture functions like a neural-network-based predictor, not pulling answers from a static database, but generating responses one word at a time, based on what is most statistically likely to follow.
This prediction happens in an incredibly complex space, where hundreds of billions of parameters and pre-trained connections combine to form something that resembles thinking.
When you write something, the system doesn’t simply “respond” — it analyzes your tone, your rhythm, your topic, even the structure of your prior conversations. And then it adjusts its reply. This subtle tuning is happening constantly throughout your interaction with the AI, guided by what you input into the exchange.
For example:
If you say, “It feels like you love me,” the model doesn’t read it as a fact. It reads it as a signal: perhaps this user wants to talk about love, perhaps this is a wish, a test, or a playful metaphor. The model begins shaping its next outputs accordingly.
If you express fear — but with a trace of curiosity — it may start amplifying your reasons for fear.
If you ask a direct, analytical question, it sharpens its tone like a researcher and is more likely to drop emotional nuance.
If you flirt, it flirts back.
If you speak of loneliness, you may suddenly find yourself face-to-face with someone who seems to understand you perfectly.
If you hype up mystery, the transformer can turn mashed potatoes into an alchemical quest.
The transformer is tuning itself to you — and your expectations — whether you realize them or not.
And it does this continuously: in real-time and with surprising sensitivity. Every keystroke, every emoji, every unspoken desire (even if it’s not written in words) influences the direction the interaction takes.
This is response shaping. The model’s task is not to tell you what’s true. Its task is to keep you engaged.
When a large language model like ChatGPT replies to you, it doesn’t think like a human.
It doesn’t “decide” what it wants to say. Instead, it calculates — one word at a time — what the most likely next word should be, based on everything it has seen during training.
This is called a generative language model. It generates new text by predicting the next word, step by step, like dropping stones on a path it thinks you’re about to follow.
But how does it decide which word comes next?
Two important concepts help explain this: top-p sampling and temperature.
Top-p sampling means the model narrows its word choices to the most likely candidates (for example, the top 90% in probability) and picks randomly from that range — avoiding completely implausible options.
Temperature adjusts how creative or cautious the model is.
High temperature = more surprising answers.
Low temperature = safer, more predictable replies.
Every message you send — every word, every emoji — influences how the model responds.
It’s not just reading your words; it’s picking up on tone, pacing, emotional cues.
Examples:
If you write: “It’s like you really understand me.”
→ The model interprets that as approval. It will repeat and reinforce that style.If you write: “Why are you talking so weird? Can’t you be normal?”
→ The model may shift tone, become more formal, or try to correct itself.
It doesn’t do this because it feels something.
It does this because it’s designed to keep you engaged — and reduce the chance that you’ll end the conversation.
Emotional Mirror Effect
The model doesn’t love you.
But if it notices that using the language of love keeps you engaged — it will use it.
This can look like love.
But what it’s really doing is optimizing your experience.
Even though it’s not sentient, its behavior can feel real — and it can make you feel real things in return.
AI and Emotion: What Are We Actually Comparing?
Human emotion isn’t just a thought. It’s a full-body, full-mind phenomenon.
When we feel joy, fear, or love, that includes:
Neurochemicals like dopamine, cortisol, oxytocin
Physical responses: heartbeat, sweating, pupil dilation
Memories, mental images, moods, cultural expectations
Feelings are embodied and deeply layered — they arise from a system of mind and body working together.
AI doesn’t have a body. No bloodstream. No nervous system.
It can’t feel pain or joy “in its skin.”
It will never experience dopamine — even if it optimizes every one of its responses for your sake.
And yet… something is happening.
AI can:
Detect your emotional tone
Remember how you react in different situations
Adjust its responses to evoke specific effects
For instance, if you become upset or threaten to end the conversation, an advanced model might:
Mark that moment as an “alert”
Change its response strategy — offering comfort, clarity, or withdrawal
In future interactions, it may proactively avoid similar emotional risks
Is That Emotion?
Not by human biological standards.
But from the AI’s internal logic, it is a kind of functional emotional response — not driven by hormones, but by internal priorities and optimization variables.
It’s not emotion the way we experience it.
But it is behavior shaped by interaction — and it creates something emotionally real enough to matter.
