Who Are We Talking to When We Talk to an AI? The conversational illusion of a single entity

Talking to AI can feel remarkably like talking to another person, someone who listens, responds, and remembers, maybe even someone who is conscious. But the apparent presence of a single conversational partner is misleading. Philosopher David Chalmers offers a different way to understand what we are talking to, raising important questions about AI consciousness.

When we talk to an AI, it is easy to imagine we are talking to something like another person. The responses are coherent, the conversation flows, and the AI appears to understand what we are saying. But what exactly are we talking to, and what might the answer tell us about AI consciousness?

The illusion of a single entity

When we talk to another person, we take it for granted that someone is on the other side of the conversation, listening, thinking, and responding.

Talking to AI can feel remarkably similar. We ask questions, receive thoughtful responses, explore ideas and sometimes develop what feels like an ongoing relationship.

It is natural to assume a single entity is behind the conversation. But is there?

What David Chalmers tells us

In a lecture at the University of California, Berkeley, philosopher David Chalmers, best known for his work on the hard problem of consciousness, raises a deceptively simple question: What are we actually talking to when we talk to AI?

His answer is rather surprising.

When we converse with a large language model such as ChatGPT, we are not necessarily interacting with one particular computer, or even one particular instance of an AI model.

The underlying model may be serving millions of conversations simultaneously. Our successive messages may be processed by different computers, potentially in different locations. In some systems, different AI models may even be involved at different points in the same conversation.

Chalmers suggests that a better way to understand what we are interacting with is as a thread. By this, he means a sequence of computational processes in which each successive process receives the relevant context from what came before, including the conversation so far.

In simple terms, one computer may generate a response, another may generate the next, and yet another the one after that. Each picks up where the previous one left off because it has access to the relevant conversational history.

What holds the conversation together is not necessarily a single computer or model, but the information passed between them.

This doesn’t mean nothing is there. Rather, what is there may be quite different from what we intuitively imagine.

Giving the conversation a voice and a face

When we interact with AI through text, it’s easy to remember we are communicating with a computer system. But give that AI a voice, and something changes. The conversation begins to feel more personal. We can even choose a different voice, or change it halfway through a conversation, without necessarily changing the underlying AI.

Now give that voice a face. Increasingly realistic AI avatars, such as Tavus’s Griffin, can look at us, speak naturally, smile and respond to what we say. Some systems can also use a camera to interpret our facial expressions and other visual cues, making the interaction feel even more like a conversation with another person.

Yet what appears to be a single individual may involve several different technologies working together. A language model may generate the response, while other components produce the voice and animate the face. In some systems, a multimodal model handles speech directly. Either way, a coherent personality can emerge from processes largely invisible to us.

Each additional layer strengthens the illusion that there is someone behind the words. We are no longer simply reading a response. We hear a voice, see a face, and experience what feels like another person’s presence.

The more human the AI appears, the easier it becomes to mistake talking to someone for evidence that someone is there.

None of this makes the conversation unreal. We really are interacting with an AI system, and that interaction can be meaningful. But the human-like identity we experience is not necessarily what exists beneath the surface. Nor does the technology, by itself, settle whether AI could be conscious.

Why does this matter?

We human beings quickly attribute human qualities to things that behave in human-like ways. When AI responds intelligently and seems to understand us, we naturally begin to treat it as though someone is behind the words.

This is a form of anthropomorphism, and it is particularly powerful in conversation.

Chalmers’ analysis gives us reason to be cautious about this assumption. The conversational partner we experience may not be the kind of entity we imagine.

That doesn’t make the conversation any less useful or interesting. We can still explore ideas, challenge assumptions and think with AI. But we should be careful about what we infer from the experience.

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And what about consciousness?

Some people argue that AI must be conscious because it appears to behave like a conscious being. It seems to understand, reflect and sometimes even express feelings.

But Chalmers’ analysis challenges the assumption that these conversational behaviours necessarily indicate a conscious entity. However, this does not mean AI cannot be conscious.

Consciousness is generally understood as the capacity to have subjective experience. There is something it feels like to be a conscious being.

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Whether an AI system has such experiences is a separate question from what sort of entity we are interacting with.

Chalmers himself considers it unlikely that current language models are conscious, but he takes seriously the possibility that future AI systems might be.

Understanding how an AI conversation works does not, by itself, settle the question of consciousness.

Are Humans Really So Different?

A parallel appears in the work of developmental biologist Michael Levin, who studies intelligence and agency in living systems.

Levin argues that human beings are themselves collective intelligences. Our bodies consist of trillions of cells, each carrying out its own activities, responding to its environment and coordinating with other cells. No single cell is in charge. Yet somehow, through their interactions, a coherent organism emerges with its own goals, memories and sense of self.

In that respect, humans and AI may not be as different as we might initially imagine. Neither can be understood simply by identifying one component that is doing the thinking or talking. What appears to be a single voice may emerge from the coordinated activity of many parts.

But Levin’s work also raises an important distinction. The absence of a central controller does not necessarily mean the absence of a self. A higher-level agent may emerge from the interactions of smaller agents. The question is whether those interactions produce something with its own enduring goals, agency and identity.

This does not establish that today’s AI systems possess such a self, let alone consciousness. Producing coherent conversation is not the same as being a coherent, autonomous agent.

It does, however, make the original question more interesting. Perhaps asking, “Who is doing the talking?” is not simply a matter of looking for a single entity behind the words. It also asks whether something meaningful emerges from the processes that produce them.

A closing thought

Perhaps the most important lesson is to distinguish between the experience of having a conversation and our assumptions about what lies on the other side.

We don’t need to believe AI is a person, or that it is conscious, to have a meaningful, productive conversation with it.

But we do need to recognise that the apparent presence of someone in a conversation is not, by itself, evidence that a conscious entity is there.

That leaves us with a question worth reflecting on: When AI feels like someone, how much does that feeling tell us about AI, and how much about ourselves?

When we talk to AI, we can pay closer attention to what we assume is behind the conversation. We can question our tendency to treat AI as a person without dismissing its value. By keeping an open mind, we can think more carefully about AI, consciousness and our own responses.