🐟 When “Fish” Don’t Exist — A Personal Starting Point
When I first heard the phrase, I laughed.
“Fish don’t exist.” It sounded like a late-night philosophical joke—something you’d say while drinking tea with overly serious friends. But it wasn’t a joke. It was, in fact, a tragic scientific truth, a declaration of failure: not just of taxonomy, but of our very human way of understanding life. (For a compelling take, see NPR’s review of Lulu Miller’s book: “Why Fish Don’t Exist Is a Biography, A Memoir — And a Scientific Detective Story”.)
The phrase originates from Lulu Miller’s extraordinary book Why Fish Don’t Exist, which traces the life of David Starr Jordan, a pioneer of American taxonomy. He named and classified thousands of species of fish. His legacy is etched in Latin across dusty museum drawers. And yet, the category of “fish” is a lie. Biologically, sharks are more closely related to cows than to rays. What we call “fish” is not a single evolutionary group—it’s a visual convenience, a simplification. A misunderstanding.
But perhaps the category collapsed not just because of biology, but because of history. Jordan was also an early eugenicist. His vision of order was rooted not only in science but in a dangerous ideology. Perhaps “fish” ceased to exist because the man who named them lost the moral right to give anything a name.
This was the moment taxonomy began to unravel for me. And it raised the deeper question: What are we really doing when we name and classify life?
Were we seeking to understand the world? Or simply to make it manageable? Convenient?
🤖 AI in Biological Classification: The End or a New Beginning?
In the age of rapid innovation, AI in biological classification is not just a tool—it is reshaping how we understand life itself. From redefining species boundaries to uncovering hidden evolutionary connections, AI is changing the way we name and know the world around us.
“There are no more species left to discover,” someone once told me in a university hallway. “Only microbes and environmental noise remain—the kinds of things only machines can sort.”
It sounded plausible. We’ve named whales and glowing squid. We’ve built trees of life and taxonomic keys. Maybe taxonomy was over.
But is it?
This isn’t just about whether we’ve found everything. It’s about whether we’ve understood anything at all.
📛 Why We Name, and Why It Fails Us
We name to make sense of the world. A child sees a flower and says “dandelion.” A biologist writes Taraxacum officinale. A neural net logs it as a cluster of digital signatures.
But the flower on a mountain trail and the one on a Seoul sidewalk—genetically, ecologically, temporally distinct—are flattened into a single name. We call that taxonomy. But what if taxonomy has always been more about utility than understanding?
Historically, naming created power and order. Yet in the age of taxonomy and AI, we are forced to ask whether that power now blinds us.
🤯 What AI Does That We Can’t
AI is miraculous. It classifies satellite images of plant ecosystems, decodes birdsong, predicts evolutionary relationships from raw DNA. It is faster, sharper, and often more accurate than humans. It creates networks we’ve never imagined.
But it doesn’t ask: Who named this? Why? What did they miss? It doesn’t feel the chill of extinction or the joy of rediscovery.
Taxonomy and AI must work together—but not as equals. One sees patterns. The other assigns meaning.
For a deeper dive into this unfolding relationship, explore the full-length reflection on this theme at Goldeners:
➡️ Taxonomy with AI: How Algorithms Are Changing the Way We Name Life
In this longform essay, you’ll find further insights, poetic metaphors, and a philosophical lens on how AI-driven classification is not ending taxonomy, but remaking it from the roots up.
Curious about the future of naming? Visit the article and join the conversation.
🧬 Naming vs Knowing
A name is not knowledge.
“Fish” groups animals by shape, not ancestry.
“Weeds” exclude plants that thrive.
“Lower animals” reinforce hierarchy, not biology.
AI may help us refine these categories, but only we can ask: What do these names reveal—and what do they erase?
This brings to mind a quietly powerful poem by Korean poet Kim Chunchu. In his poem 꽃 (The Flower), he writes:
내가 그의 이름을 불러주기 전에는
그는 다만
하나의 몸짓에 지나지 않았다
내가 그의 이름을 불러주었을 때
그는 나에게로 와서
꽃이 되었다
Before I called his name,
he was nothing more
than a fleeting gesture.
But once I called his name,
he came to me
and became a flower.
This poem distills the magic and responsibility of naming. It suggests that naming is not simply a label we impose—it is a kind of love, a recognition that brings something or someone into the center of our attention, our care. Without that act, the world remains mute, unacknowledged. But with it, it becomes intimate, alive.
And so, when we speak of taxonomy and AI, we are not merely talking about systems. We are talking about relationships. About what becomes visible when we choose to name—and what still waits to bloom when we don’t.?
🌱 Classification Is Not Ending—It’s Transforming into Something Wilder and Wiser
For a while, it did seem like taxonomy had run its course.
The big names had been named. The dazzling megafauna catalogued. The forests mapped, the fish sorted, the phylogenetic trees drawn and redrawn. A field once charged with discovery seemed—at least to some—finished. But that impression was only ever an illusion.
Because the wild doesn’t stop moving just because we’ve given it a name.
Taxonomy, like the living world it seeks to describe, is shedding its old skin. It is not dying. It is molting. And from that fragile, incomplete rupture, something new is emerging—something stranger, more fluid, and more alive.
What we need now is not more rigid categories, but questions that bloom:
- Not fixed definitions, but relationships that evolve
- Not static drawers, but ecologies that pulse and shift
- Not binary classifications, but a spectrum of becoming
This is not the death of taxonomy. This is its return to life.
AI in biological classification may give us new tools and dazzling speed, but the true challenge is to remain attuned to the hum beneath the data—to the tangled symphonies of evolution and ecology that refuse to fit into neat boxes.
In this renewed vision, classification becomes not a system, but a conversation. Not the imposition of order, but the invitation to notice, to wonder, to dwell.
Taxonomy is not over. It is, at last, becoming what it was always meant to be: a living language for a living world.
EEAT: Why This Perspective Matters
This reflection is grounded in the principles of Experience, Expertise, Authoritativeness, and Trustworthiness (EEAT):
- Experience: Rooted in firsthand engagement with biodiversity research, taxonomic archives, and machine-learning models for ecological classification.
- Expertise: Authored by a scientist with a graduate degree in molecular biology and evolutionary theory, with applied experience in data-driven taxonomy.
- Authoritativeness: The discussion references recognized sources such as Systematic Biology, Trends in Ecology & Evolution, and real-time AI bioinformatics initiatives.
- Trustworthiness: Ethically grounded with sensitivity to cultural, historical, and Indigenous naming systems, including critique of problematic legacies in taxonomy.
🧭 From Categorizing to Caring
If the machine classifies, we must remember. AI gives us outlines; we must supply the intention. This is the challenge of taxonomy and AI—not to surrender to automation, but to create a new ecology of meaning.
Because naming is never neutral. It is memory. Power. Responsibility.
Let the future of taxonomy be more than technical. Let it be deeply human.
External Links:
This essay was initially inspired by Lulu Miller’s Why Fish Don’t Exist, a deeply affecting meditation on the collapse of taxonomic certainty and the perilous intersection between scientific classification and human ideology. The story of David Starr Jordan is a stark reminder that naming is never apolitical—and that AI, too, must be held to standards of meaning, not just accuracy.
- Nature Communications – Machine Learning in Phylogenetics
- Trends in Ecology & Evolution – Naming Biodiversity
- Systematic Biology – Algorithmic Taxonomy
Focus Keyword: taxonomy and AI
Related Keywords: AI in biological classification, naming and meaning, future of taxonomy, post-Linnaean classification, ethics of naming in biology
