Written by Joss Duggan (Reading Time: 15 mins)

The Mind’s Changing Reflection

For thousands of years, we've looked at the tools we build and seen ourselves in them. Every era’s most advanced technology has shaped the way we imagine the human mind - an aqueduct, a clock, a telephone switchboard, a computer. We build machines to enhance our world, but in the process, we use them to describe our inner world as well.

This is more than just a linguistic trick. The metaphors we choose for the mind shape how we try to understand it. They dictate the questions we ask, the limits we impose, the very possibilities we consider.

But what if, in doing so, we are trapping ourselves in the assumptions of our own time?

If the best technology of today is how we explain the mind, will our current models - computation, AI, neural networks - eventually seem as quaint as describing emotions as flowing humours, or ideas as steam?

Ancient Metaphors: Water, Pneuma, and Mechanical Motion

Long before circuits and algorithms, ancient civilisations sought to explain thought through what they understood best: the movement of natural forces.

For the Greeks and Romans, the dominant metaphor was flow. The body was a system of humours, fluids coursing through channels like an aqueduct distributing water to a city. The mind was governed by the balance of these flows - an excess of bile or blood leading to moods, energy, or sluggishness. To manipulate thought or emotion was to control this movement, much like a physician or engineer adjusting the flow of a system.

““You can’t step into the same river twice””

— Heraclitus

Another early metaphor came from the Stoics, who described the mind as powered by pneuma, a kind of vital air or breath that animated the body. Thought was not something static but a force in motion, like wind through an instrument. This model influenced early medical and philosophical theories, shaping concepts of human vitality and agency.

Then came the mechanical metaphor, shaped by the growing sophistication of early engineering. Greek thinkers like Hero of Alexandria, who built early automatons, compared cognition to a catapult - a process of loading, aiming, and firing ideas into action. Thought, in this view, was a mechanical force: primed, released, and directed.

This metaphor expanded as early automata and clockwork devices became more refined, suggesting that the brain might operate under predictable physical laws, much like engineered structures. Ancient Chinese and Indian scholars also developed similar analogies, seeing the mind as an intricate mechanism that could be tuned or balanced to maintain order and function.

The Takeaway: The earliest metaphors tied cognition to the natural world - fluid motion, breath, and force - reflecting an intuitive understanding of the body as part of the environment.

The Clockwork Mind: Mechanisation and Dualism

The Renaissance and Enlightenment saw the rise of clockwork machines, some of the first human-made devices capable of precise, predictable motion. It was only natural that the metaphor shifted accordingly.

Descartes provided one of the most influential versions: the body as a mechanical system, controlled by a separate, rational mind - the famous ghost in the machine. He likened the nervous system to pipes and levers, the body responding like an automaton, with the soul as the unseen pilot. This dualistic perspective laid the groundwork for centuries of debate about the mind-body relationship.

Unsurprisingly, as clocks became more advanced, so did the metaphor. The brain was no longer just a machine - it was a self-regulating gear system, a complex but deterministic mechanism grinding away beneath the surface of conscious thought. The precision of mechanical timepieces inspired thinkers to conceptualise cognition as a series of interlocking parts, each functioning predictably and governed by logical principles.

“The body is a machine, the mind its pilot”

— René Descartes

This period of history also introduced mechanical automata, complex devices mimicking human movement and action. As engineers like Jacques de Vaucanson created lifelike machines that moved, played instruments, and mimicked speech, the idea that cognition could be reduced to mechanical interactions gained traction. Thinkers like Leibniz even suggested that if one could build a machine small enough, one might peer inside the workings of thought itself.

The Takeaway: The clockwork metaphor introduced the idea of deterministic cognition - a structured, rule-based system that ticked along predictably, setting the stage for later computational views.

The Steam-Powered Psyche: Thermodynamics and Mental Energy

With the Industrial Revolution came steam engines, which fundamentally changed how people viewed power, work, and motion. Just as machines needed fuel to produce energy, so too did the human mind seem to function under principles of energy conservation, release, and conversion.

Freud’s model of the psyche was deeply influenced by thermodynamic principles. He saw the mind as a pressure system, where unconscious drives built up like steam in a closed chamber. If not released through appropriate channels, these pressures could result in emotional distress or breakdowns. Neuroses were viewed as blockages in this system, requiring controlled release through therapy to restore equilibrium.

Beyond Freud, other psychologists adopted similar energetic metaphors. Mental effort was increasingly described in energetic terms - exhaustion as a depletion of cognitive resources, focus as an investment of energy, and emotional distress as a buildup of unresolved pressures.

By the late 19th century, Wilhelm Wundt and others explored reaction times and neural excitations in terms of energy conversion, seeing the brain as a metabolic system where cognitive exertion followed physical principles.

The Takeaway: The industrial age introduced the idea of the mind as an energy system, where thoughts and emotions operated under laws of thermodynamics.

The Mind as a Telegraph and Telephone Switchboard

The rise of telephone switchboards in the late 19th and early 20th centuries revolutionized communication, and with it came a new metaphor for the mind. Just as operators connected calls by plugging and unplugging wires, early neuroscientists imagined the brain as a vast switchboard, relaying signals between different regions to produce thought, memory, and action.

One of the most significant proponents of this idea was Charles Sherrington, who described the nervous system as an “integrative action” of circuits, with neurons acting as electrical relays. His work laid the foundation for the modern understanding of synaptic transmission, in which thoughts are transferred like calls bouncing from switchboard to switchboard across the brain’s vast network.

“Man is but a network of relationships and circuits”

— Norbert Weiner

This analogy also paralleled the development of cybernetics in the mid-20th century. Thinkers like Norbert Wiener extended the metaphor, likening the human mind to an information-processing system—capable of adjusting, rerouting, and optimizing signals based on feedback, much like an advanced switchboard operator directing an overwhelming influx of calls.

Yet, the metaphor had its limitations. Unlike a telephone exchange, which relies on deliberate human input, the brain is not merely a passive relay station—it adapts, learns, and sometimes misroutes information in ways that a rigid switchboard could never do. Nonetheless, this concept paved the way for later computational theories of mind and early AI research, reinforcing the idea that intelligence could be mechanized and optimized through structured connections.

The Takeaway: The rise of electrical networks reinforced the idea of thought as structured signal transmission, a precursor to modern neuroscience and AI models.

The Mind as a Computer: Symbolic Processing and AI

Have you tried turning it off, and on again?

As the 20th century progressed, computers emerged as the dominant technology, and with them came a radical shift in how we conceived of the mind. No longer a system of mechanical parts or flowing energy, cognition was now understood as symbolic processing - a set of rules for manipulating information, akin to the logic gates of a machine.

The Turing Machine, conceptualized by Alan Turing in the 1930s, provided a foundation for this metaphor. Turing proposed that computation could be broken down into discrete, programmable steps, leading to the idea that thought itself could be reduced to a series of logical operations. This view fueled the rise of cognitive science, where researchers likened memory to digital storage, reasoning to computational algorithms, and perception to data input.

“A man provided with paper, pencil, and rubber, and subject to strict discipline, is in effect a universal machine”

— Alan Turing

This model became dominant in the mid-20th century, particularly with the advent of artificial intelligence (AI). Early AI pioneers, such as John McCarthy and Marvin Minsky, pursued the dream of creating machines that could think like humans by encoding knowledge as a series of rules and logical structures. The mind as a computer became the standard metaphor in psychology, neuroscience, and philosophy of mind.

Yet, as AI developed, it became clear that human cognition was not simply a matter of logical processing. The failures of early AI to replicate human creativity, intuition, and learning forced a re-evaluation of the computational metaphor.

The Takeaway: The computer metaphor dominated the 20th century, but it struggled to fully explain human cognition, leading researchers to explore more dynamic and adaptive models.

The Neural Network Model: The Mind as an Adaptive System

The metaphor of the brain as a computer began to falter as neuroscientists realized that cognition was not a rigid, rule-based process but an adaptive, dynamic system. Enter neural networks, a conceptual shift that mirrored how the brain actually functions—not as a series of predefined circuits, but as a constantly evolving system of connections that strengthen or weaken over time.

Unlike traditional computational models, which rely on explicitly programmed logic, neural networks operate through learning and experience. Inspired by the biological structure of neurons, artificial neural networks mimic how synapses adjust their strength based on repeated patterns of activity, leading to the development of deep learning and artificial intelligence that can recognize patterns, make predictions, and even generate new information.

“The brain is the most complex thing we have yet discovered in our universe”

— Michio Kaku

This shift reflected a deeper understanding of neuroplasticity, the brain’s ability to rewire itself in response to injury, learning, and environmental changes. Rather than functioning like a static, mechanical system, the brain reconfigures itself over time, making intelligence more about adaptation than computation.

However, while neural networks have revolutionised AI, they have also highlighted limitations in our understanding of consciousness. AI systems can process vast amounts of data and optimise performance through feedback, but do they understand? Unlike the human brain, which integrates sensory experience, emotion, and abstract reasoning, artificial neural networks lack an intrinsic sense of meaning—they recognise patterns but do not perceive them.

Despite this, the neural network metaphor has been instrumental in reshaping modern neuroscience, leading to breakthroughs in deep learning, cognitive psychology, and even theories of memory formation and decision-making.

The Takeaway: The neural network model moved beyond the rigid computational metaphor, suggesting that cognition is fundamentally about adaptation and experience-driven learning.

The Quantum Mind: A New Frontier?

While neural networks offer a more biologically plausible model of cognition, they still operate within classical physics. However, recent explorations into quantum mechanics have led some researchers to propose that consciousness itself may be a quantum phenomenon.

The Orchestrated Objective Reduction (Orch-OR) theory, developed by physicist Roger Penrose and anesthesiologist Stuart Hameroff, suggests that consciousness arises from quantum processes within microtubules in neurons. Unlike classical computing, where bits exist in states of 0 or 1, quantum computing allows for superpositions, where multiple possibilities can exist simultaneously.

If cognition operates at a quantum level, it could explain aspects of human thought that remain mysterious—such as intuition, creativity, and even free will. While still controversial, the quantum mind hypothesis forces us to ask: Have all previous metaphors been insufficient because they rely on classical mechanics, while the mind itself may operate in a fundamentally different way?

The Takeaway: If consciousness has quantum underpinnings, then all previous mechanical metaphors may be inadequate, requiring a radical new framework for understanding the mind.

Conclusion: Beyond Metaphors?

From flowing humours to clockwork gears, from telegraph circuits to neural networks, our attempts to understand consciousness have always been shaped by the technology of the time. Each metaphor has provided valuable insights but has also imposed limitations, framing cognition within the boundaries of human invention.

But what if consciousness isn’t like any of these things? What if the mind is not a machine, not an energy system, not a computer, but something entirely different - something we have yet to fully conceptualise?

As science progresses, new paradigms will emerge, bringing new metaphors with them. Perhaps future discoveries will force us to abandon technological analogies altogether, replacing them with something closer to reality. Until then, we will continue to peer into the mind’s depths, using the tools at our disposal to try and capture something that may, ultimately, be beyond metaphor itself.

The Final Takeaway: Our metaphors for the mind have evolved with our technology, but the ultimate nature of consciousness may require an understanding beyond machines, networks, or computations - something we have yet to even imagine.

To Sum Up

Rivers and Aqueducts – Thought flows like water through channels, requiring structure but always moving (Heraclitus)
Ballistics and Catapults – Ideas are launched like projectiles, calculated but influenced by external forces (Ancient Ballistics)
Clockwork Mechanisms – The brain is a system of gears and levers, ticking predictably (Descartes)
Steam and Pressure Systems – The psyche builds up mental energy like a closed system that must be released (Freud)
Electrical Circuits and Switchboards – Thought operates through pathways of connection, relaying signals like a vast network (Sherrington)
Computers and Algorithms – Computation explains intelligence (Putnam & Fodor)
Neural Networks – The mind isn’t programmed; it learns rewires, and adapts.
Quantum Computing – If the brain operates at a quantum level, all previous metaphors might be obsolete (Roger Penrose)
Final Thought – Every era’s technology reshapes our view of the mind. But what if the mind is not like any of our inventions? We may need an entirely new paradigm - or to accept that some things simply defy metaphor.

Metaphorical Minds: How we describe mental life