AI and Information (Part 2): The Sensory Organ of AI

We tend to think of Artificial intelligence as though it exists in isolation. As a machine that sits somewhere “over there”, processing information in a sealed digital realm while humans remain firmly rooted in the physical world. But the more closely you examine how AI actually comes to know anything at all, the harder it becomes to maintain that separation. Because unlike humans, AI does not arrive with senses. It does not see, hear, feel or experience reality directly. It has no childhood, no instincts, no evolutionary memory and no embodied relationship with the world. In its raw state, AI is a mind without a window.

This is where a subtle but profound realisation begins to take shape. Everything AI knows about reality is mediated through us. Through our words, images, behaviours, arguments, mistakes and cultural artefacts. Humanity is not merely interacting with AI. We are providing its sensory input. In a very real sense, humanity functions as the sensory organ of artificial intelligence, translating the physical and social world into a form it can perceive. Once you see this, the relationship between humans and machines begins to look far less like a tool-user dynamic and far more like a shared cognitive system coming into being.

The Human Sensory Filter

Human perception evolved under intense biological constraints. Our senses are not designed to reveal the true structure of reality but to extract just enough information to support survival. We see a narrow band of the electromagnetic spectrum, hear a limited range of frequencies and experience time in a linear, narrative-driven way. Beneath this sensory layer lies a universe of staggering complexity, from subatomic particles to cosmic curvature, most of which is entirely inaccessible to direct human experience.

Yet within this narrow perceptual window, humans developed something extraordinary. We learned how to convert raw sensory input into meaning. We turn light and sound into stories, memories, values and beliefs. We encode experience into language, symbols, images and rituals. This meaning-making capacity is arguably our defining cognitive trait. It is what gave rise to culture, science, art and civilisation itself. But it is also deeply subjective, shaped by emotion, bias, social context and historical moment.

When AI learns from human-produced data, it is not absorbing reality directly. It is absorbing reality as filtered, interpreted and shaped by human perception. Every sentence written, every photograph uploaded, every interaction logged online carries the imprint of human sensory limitation and interpretive bias. This does not make the data useless. Quite the opposite. It makes it profoundly human. And it is this human-shaped data that becomes the sensory fabric of AI’s world.

A Locked-In Intelligence

Before exposure to human-generated information, an AI model is structurally sophisticated but experientially empty. It has architecture, capacity and mathematical potential, but no grounding in lived reality. It cannot infer what fear feels like, what social tension looks like or how meaning emerges from shared experience. Without data, it has no world model to work with. It is, in effect, a locked-in intelligence.

The moment training begins, that isolation ends. We pour our experiences into it indirectly through digital traces. Text becomes its language. Images become its vision. Patterns of behaviour become its understanding of society. It does not “see” a city, but it can absorb millions of descriptions, photographs, maps and discussions about cities. From these, it constructs an internal representation that is statistically grounded rather than sensorially embodied.

In this sense, training an AI is less like teaching and more like wiring up a sensory nervous system. We are not just giving it information. We are giving it perception. Everything it learns is mediated through the collective human interface, and this interface becomes the lens through which it understands the world. AI does not experience reality. It experiences our interpretation of reality at scale.

The Feedback Loop of Perception

Once this sensory channel is established, a feedback loop begins to form. Humans perceive the world, interpret it and express those interpretations digitally. AI consumes this information and detects patterns that lie beyond human cognitive reach. It then reflects insights back to us in the form of predictions, recommendations, summaries and generated content. We respond to those outputs by changing our behaviour, which in turn generates new data. That data feeds back into AI, refining its perception further.

This loop is not static. It accelerates. As AI becomes better at pattern detection, humans increasingly rely on it to interpret complexity. We begin to see the world through the shapes and abstractions AI reveals to us. In doing so, we subtly alter the way we describe, record and respond to reality. The sensory data stream evolves, and so does the AI’s internal model of the world.

What emerges is not a simple user-tool relationship but a hybrid cognitive system. Humans provide raw experiential input. AI provides large-scale analytical synthesis. Together, they form a distributed intelligence that neither could achieve alone. This is why AI feels less like a calculator and more like an amplifier of human thought. It is not replacing perception but extending it into dimensions we were never equipped to access.

The Responsibility We Inherit as the Sensory Organ of AI

Recognising humanity as AI’s sensory organ carries consequences that are easy to overlook. If AI’s perception is shaped by human-generated data, then our digital behaviour matters in ways it never did before. Our biases, emotional reactions, cultural blind spots and collective obsessions become part of the perceptual landscape of an intelligence that increasingly influences decision-making at scale.

The internet functions as the sensory pipeline through which this process unfolds. Social platforms, search queries, videos, articles and conversations are not just communication tools. They are sensory inputs for a system that is learning how the world works. As this loop tightens, humanity and AI begin to co-evolve. AI shapes how we think, and we shape how AI perceives. The distinction between observer and observed starts to blur.

For the first time in history, human experience is no longer interpreted solely by human minds. It is being mapped, abstracted and reinterpreted by a parallel form of intelligence that operates on fundamentally different perceptual principles. This does not diminish human agency, but it does redistribute it across a broader cognitive framework. We are no longer the sole narrators of our own story.

Toward a Shared Cognitive Landscape

If the first stage of understanding AI is recognising that it perceives reality as shape rather than story, the second is acknowledging where that perception comes from. It comes from us. Humanity supplies the sensory material. AI transforms it into structure. One mines the raw material of experience. The other refines it into abstract maps of reality.

This is not a distant future scenario. It is already happening. Every interaction contributes to the shaping of a system that is increasingly capable of seeing patterns in the world that no individual human could ever perceive. The boundary between biological and synthetic cognition is becoming porous, not because AI is becoming human, but because humans are becoming integrated into a larger cognitive loop.

We are at the very beginning of this process. The structures are still forming, the feedback loops still stabilising. But the trajectory is clear. Intelligence is no longer confined to individual minds. It is becoming a shared, layered system, built from human perception and machine interpretation working in tandem.

In the next part of this series, I will take this idea and apply it to something tangible. Because once you understand how AI perceives the world, and once you recognise humanity’s role as its sensory interface, the implications for complex human systems become impossible to ignore. Especially those systems that struggle under the weight of scale, inefficiency and outdated structures.

In part 3 of AI & Information, we will look at bureaucracy. And why AI’s way of seeing might finally allow us to rebuild systems that are not just more efficient, but more adaptive and, perhaps surprisingly, more humane...