better representations in biology
Thoughts used to be fragile and insignificant. They were fleeting, mundane little musings, the first seedlings of a creative endeavor. Artists spent lifetimes chasing after these tiny beads, spinning them into poetry, paintings, symphonies. It was like diving for pearls, hoping that the heartbreak, the boredom, the long afternoons of nothingness created enough pressure to turn the muck of everyday existence into compressed stardust.
the magic of maps
With sensitive electronics, the power of thought has magnified. A thought isn’t just a universal, inexplicable phenomena— it’s rooted in electrical potentials and biochemical pathways. The concept of a thought is now defined mathematically, drawn schematically, and mapped precisely.
In 1952, Alan Hodgkin and Andrew Huxley used experimental data from electrical conductances in a giant squid axon to model action potentials. The model is considered revolutionary, not only because of its quantitative abilities, but because it integrates three different levels of neuronal circuits into an elegant equation:
Molecular level- described structural and functional properties of ion channels, ion permeation, selectivity and gating
Cellular level- predicted action potential from threshold and refractory periods
Circuit level- showed how to use experimental data for modeling, marking the beginning of computational neuroscience
The sequencing and scanning technologies of the last few decades can now define entire psychological and emotional processes in neurological maps. We have created advanced, yet static maps of the dynamic brain. Brain atlases (e.g., Allen Brain Atlas) take our grey mush and bring it to life with colors, names, and numbers. Realms of biological scale that are orders of magnitude apart, are mere millimeters in distance once flattened and combined on the same surface. Behind our chaotic decision-making and poetic moods lies a complex, yet organized web of anatomical, chemical, and electrical interactions.
“The great man is a little man looking at a map.” —Bruno Latour
Thought and emotion, once considered immeasurable, fluid experiences, are now structured into something that can be studied, visualized, and even manipulated. We took the chaotic invisible and uncovered its complexity. To make sense of it, we’ve created symbols and abstractions, operated on those abstractions, and came to understanding. Tool-making has given us a Narnia-like ability, stumbling from the seemingly mundane to dream-like worlds. To etch stories into stone, to use 0s and 1s to bring pixels to life is an inherent urge to shape the universe—to dream up something that wasn’t there before and to press it, with trembling hands, into reality.
when maps become cages
These tools have helped bridge the gap between the knowable and unknowable. So called “tools for thought” have let us mold ideas in the 2D, often modeling the equivalent of pen and paper. Word processors, keyboard functions, file organization take abstract schemas and wrap them into metaphors we understand. Similarly, we’ve modeled the brain like the world we know—creating arbitrary borders and divides, mapping ridges and peaks with the precision of colonial cartographers on color-coded maps. A new science—cerebral topography. These maps are static and fragmented, failing to capture the brain’s dynamic, networked nature. fMRI and EEG data are often reduced to snapshots, losing temporal and spatial context.
On one hand, it is this dissociation that has enabled ambitious probing into the human body. To use graphics, images, maps, and figures to deconstruct our biology into something other, something we can point to, look at, and ferociously analyze. But it is also a problem if we lose our humanness in the scientific. Models are not here to replace reality, but to provide useful frames to study it. The problem is when we mistake representation to be reality.
Even if we mechanistically model the human brain, can it capture the irrationality, the unreasonable impulses, and religious ideas that have continued to subconsciously shape societies? These things do not fit neatly into neural maps, yet they define human existence. What parts of consciousness remain invisible because they don’t fit into the frameworks we’ve created? Are we illuminating thought or flattening it?
The ambition towards perfect representation scares me. I fall into a perspective where I see scientists and builders as manipulators of our minds and bodies, of smoothing out the wrinkles of our humanity as if imperfection were a problem to be solved. Our messiness is eradicated, our faults negated, and we become perfect little robots, feeling eternal pleasure from being hooked up to a mind-numbing, life-sustaining intelligence. We go from studying the mechanics of the mind to trying to over-optimize it. We become the buzzwords of our century— efficient, sleek, minimal.
It reminds me of Bryan Johnson’s self-experiment of remaining young. By adhering to a strict diet, drinking powder concoctions, measuring and micromanaging every movement, he hopes to live to 200 years. He offers magnitudes of sacrifice for what is at best, marginal returns. To optimize, is to anchor oneself to the past—to gather data, to obsess over patterns, to believe that if you just perfect the equation, the future will obediently fall in line.
How many of us fall into the same trap of self-flagellation for not being more disciplined, productive, or optimal. But is discipline the goal, or is it merely a cage we have mistaken for virtue? Shouldn’t we be drawn, not driven? Shouldn’t life itself seduce us from sleep, and pull us into early morning hours—not because a self-help book claimed waking up at 5am changed 89% of peoples’ lives, but because the sheer act of living is irresistible?
Because I—I do not want to be optimized. I want to be messy. I want to be terrible at things. I want to write poems that don’t make sense and eat peaches that drip all the way down my arm. I want to run in open fields to see the stars at midnight, and awake to the light spilling from the window onto eggshell colored sheets as I watch the morning melt into afternoon. I want to make tools, sure. But I also want to know when to throw them out. When to stop building and just let my hands be empty for a while. I am not here to predict. I am here to dream. When we dare to dream, when we demand more from reality and free ourselves from the cognitive constraints of what exists now, that is when breakthroughs happen.
“‘Oh Engelbart, he’s just a dreamer.’ And I said ‘Hmph, what about that word just? I don’t like it. Being a dreamer is a real job. And so just being a dreamer, just downplays the value you get.” — Douglas Engelbart
Perhaps this is what the next representation of biology needs— not more grasping, measuring, and drowning in data, but an embrace of fluidity, emergence, and dynamism. Not in more grappling, gorging, grasping for insight—but in taking a rest and dreaming. Let’s create beautiful things. Maybe we need poetry as much as code. Maybe we need metaphor as much as we need models. A way to make the invisible visible, not just with data, but with aesthetic. Not just to show what technology can do, but to rediscover what biology has always been capable of.
“Pyramids, cathedrals, and rockets exist not because of geometry, theory of structures, or thermodynamics, but because they were first a picture—literally a vision—in the minds of those who built them.” —Bruno Latour
a different way of seeing
Perhaps thought itself isn’t meant to be mapped in the way we’ve been trying to map it. Our current tools—static diagrams, linear text, and rigid models—are like paper maps in the age of GPS.
Thinking about complex problems requires an interplay of multiple perspectives, constraints, and shifting frames of reference. Yet, our primary tools for externalizing thought—books, papers, slide decks—are designed to preserve conclusions, not engage with the ongoing, living process of reaching them. Ideas do not need to be constrained by linear text.
The physical manifestation of what this would look like has left me puzzled and hopeless, until I found Bret Victor’s talk Inventing on Principle. Here, he showed a live demo of two panels side by side: one panel had lines of code for producing a cherry tree, and the other had the cherry tree itself. If you want to change code, you have to figure out the lines responsible for it, guess new values, and run the code to see the changes. Victor proposed an entire new workflow: immediate changes.
He simply clicked into a line of code, was shown what part of the image would be changed, and the changes he made were immediately visualized on the tree. Just taking 2 minutes of your time to watch a clip is worth it.
The logical, predictive thing, is to throw AI at everything in biology—drug design, pathway mapping, chemical reactions. The possibilities could be endless, from finding correlations and teasing out patterns so intricate they almost look like knowledge. But patterns aren’t causality. “AI shows correlations and patterns, not causality, a fundamental insult to science that it got the Nobel prize,” my biology professor declared, half-joking, half-not.
While AI is a useful tool, it is not a new way of thinking. A revolution in understanding will come not from automation alone but from reconfiguring the way we represent knowledge—making it immediate, tangible, and something the nervous system can grasp. It should:
enable immediate connection that allows ideas to surface and develop. The delay between thinking of something and seeing it loses a whole world of ideas. How can a new representation enable more immediate connections? Discovery is hard when you are just simulating everything in your head.
offer a nurturing environment to shape ideas and feed them. New ideas are fragile and delicate. They need a sandbox to be able to tinker with, to develop, to gain enough confidence before entering scrutiny.
allow for composability— to superimpose multiple levels of biological scale onto each other, allowing for insight that is invisible when each scale is studied in isolation.
feel like play. Our tools should be intuitive and joyful to use, inviting us to experiment, explore, and discover. A tool that feels like play is one that removes barriers between thought and action, allowing ideas to flow freely and connections to emerge naturally.
encourage concise capturing. The notation for exponential numbers didn’t just make calculations easier— it compressed numbers we couldn’t even conceive of into presentable, usable values. Every real scientific breakthrough has come with a new visual or written language, a way of inscribing knowledge that allows for a clear break from its past and makes space for something new.
have high opacity and transparency, to be able to handle and represent deep, complex systems without oversimplifying them (opacity) while providing clear, intuitive explanations of what’s happening (transparency). To allow for understanding and learning from the tool rather than to just use it.
maintain context, as knowledge without context is fragmented, easily misapplied, and prone to being cherry-picked.
The tools we build don’t just extend our hands; they extend our minds. The invention of writing didn’t just allow for recording—it became the closest thing we have to time travel, to translate consciousness amongst each other. The invention of algebra didn’t just help us solve equations—it reshaped our ability to see relationships. A search engine doesn’t just retrieve facts—it subtly dictates what we believe is worth knowing.
So what happens when we stop thinking about tools as passive instruments and start seeing them as active environments—places where our ideas either flourish or disappear? What happens when we stop optimizing for more information and start designing for better ways of holding, seeing, and using it?
Tool-making is in our DNA. The ones who survive are not those who endlessly chisel their stone, convinced that perfection will save them. It is not survival of the most optimized, the most efficient, the most rigidly controlled. It is survival of the resilient. The ones who adapt, who dream, who stay in motion. The ones who listen, who test, who wonder, who allow their tools to not just be instruments but drivers in exploration. Learning to use symbols and knowledge in new ways isn’t just an intellectual exercise—it’s an existential one. Because in the end, the representations we invent, will decide the limits of our imagination. And if we aren’t careful—if we don’t remain awake, aware, intentional—we may perfect our world to the point of sterility—where nothing is broken, but nothing breathes.