What If SETI Has Been Looking for the Wrong Thing?
What If SETI Has Been Looking for the Wrong Thing?
Signals, Meaning, and a Universal Semantic Rune System
For more than half a century, the Search for Extraterrestrial Intelligence (SETI) has listened to the sky for odd signals: narrow-band radio spikes, repeating pulses, anything that doesn’t look like the usual astrophysical noise. The standard picture is romantic and simple: one day, a graph on a monitor will show a pattern so unmistakably artificial that we’ll say, “Someone is saying hello.”
But there’s a deeper, harder problem hiding behind that fantasy: even if we did receive a message, how would we know what it means?
That question has led me into a peculiar project: designing a symbolic system that tries to capture meaning itself—before any particular human language. It’s called the Universal Semantic Rune System (USRS). It started as a way to think more clearly about human and machine cognition, but it turns out to have surprising relevance for SETI.
This essay is about that intersection: what happens when you stop asking, “Can we detect a signal?” and start asking, “Can we recognize a mind?”
From Signals to Signs
Most SETI work treats a “message” as a physical phenomenon: a radio wave, a laser pulse, maybe one day a neutrino beam. We analyze its frequency, strength, and periodicity. Is it too clean to be natural? Is the pattern too orderly to be random?
All of that is about signal. But meaning lives one level up, in the realm of signs.
A sign is anything that stands for something else: a word for an object, a symbol for an idea, a diagram for a process. Semiotics—the study of signs—doesn’t care about the physical medium as much as the structure of substitution: how one thing systematically “means” another.
USRS starts from this semiotic perspective. Instead of asking, “What kind of radio signal would aliens send?”, it asks, “What sort of abstract structures would any intelligence use to represent its world?” In other words: if minds rhyme, what is the rhyme scheme?
A Conceptual Operating System, Not a Language
USRS is not a new spoken language with its own alphabet and grammar. It’s closer to a conceptual operating system: a way of encoding thoughts that tries to be independent of any particular tongue, culture, or vocal apparatus.
It does this in four layers:
Core primitives
At the base are “semantic atoms”: very simple, irreducible concepts that appear to show up in every human language. Things like:something exists
something happens
one thing causes another
a part belongs to a whole
something is good or bad
something happens before or after something else
These aren’t words; they’re meanings that words in different languages all circle around.
Composite symbols
These primitives are represented by visual symbols—runes—that are not tied to any existing alphabet. You can combine them into more complex symbols to represent richer ideas: “an event of water falling from the sky,” “a state of the ground being wet,” “an agent that wants something.”Modulation and nuance
On top of this, you can overlay modifiers that express attitude, intensity, or strategic stance: is this a warning, an invitation, a threat, a joke? These don’t change the core facts, but they color how they’re meant.Structural grammar
Finally, USRS has rules for how these elements relate to each other in time and causality: if this, then that; because of this; despite that; before this; after that. It’s a way of drawing the skeleton of a story or an argument.
Put together, these layers form a symbolic toolkit for describing what’s happening, who is involved, and how events hang together—without committing to any specific human language or script.
A Tiny Example: When It Rains
Concrete examples help. Consider this simple bit of reasoning:
If it rains, the ground gets wet.
It is raining.
Therefore, the ground is wet.
In everyday life, we don’t think twice about this. But inside USRS, it becomes a small structure of primitives and relations.
First, we identify a few elemental ideas:
an event of rain (water-from-sky happens)
a state of the ground being wet
a causal link: the rain makes the ground wet
a temporal marker: now
Then we draw a little conceptual graph:
a node for RAIN-EVENT
a node for GROUND-WET
an arrow from RAIN-EVENT to GROUND-WET labeled “makes” or “leads to”
a marker that says “RAIN-EVENT is happening now”
From that structure, a simple rule applies:
if RAIN-EVENT leads to GROUND-WET, and RAIN-EVENT is happening now, then GROUND-WET is happening now.
Notice what’s absent: no English, no sound, no cultural metaphors. Just events, states, and a causal template.
This pattern is not uniquely human. Any intelligence that predicts its environment—biological or artificial, on Earth or elsewhere—has to grapple with “if X, then Y” in some form. USRS tries to write that form down.
Why This Matters for SETI
So far, this may sound like an exercise in cognitive minimalism. How does it help us with extraterrestrials?
Because most SETI thinking quietly assumes that once we spot a signal, decoding is mostly a matter of clever pattern analysis and math. But to actually understand a message, we need to reconstruct the sender’s internal distinctions: what they take to be an event, a cause, a state, an agent, a goal.
USRS offers a way to look for those distinctions structurally, even when we don’t know the symbols.
Imagine we intercept a long, structured sequence of unknown glyphs or pulses. Instead of asking, “What word does this stand for?”, we ask:
Do some patterns reliably precede others, the way causes precede effects?
Are there recurring clusters that behave like “concepts”—appearing intact in different contexts?
Can we hypothesize something like “if A, then B” structures and test whether they predict parts of the sequence?
Using USRS as a reference, we’d try to map these unknown patterns onto a small set of universal conceptual roles: event, state, cause, condition, before, after. We might be wrong at first, but we’d have a systematic way to propose and refine structural hypotheses.
This mirrors how researchers study undeciphered human scripts like rongorongo or ancient Maya writing: you start with patterns and structure, not vocabulary. USRS adds a formal, explicitly cross-linguistic concept layer to that structural approach.
Forcing AI to Think in Runes
There’s another angle where USRS and SETI intersect: artificial intelligence.
Modern AI systems—like large language models—do their internal work in high‑dimensional numerical spaces. They’re astonishingly good at prediction, but their “reasoning” is inscrutable. We see inputs and outputs, but the middle is a blur.
One of the more ambitious goals of USRS is to make AI inhabit this symbolic space for at least some of its thinking. Instead of just mapping:
words → numbers → words,
we ask the system to map:
words → USRS graph of primitives and relations → (possibly updated) USRS graph → words.
The crucial part is the middle: the graph. Each node is a concept (event, state, agent), each edge a relation (causes, prevents, depends on, happens before). The AI’s “thought” becomes a sequence of graph transformations that we can inspect, criticize, and refine.
Why does this matter for SETI?
Because learning to read and work with non-human, graph-like representations of thought in our own machines is excellent practice for encountering something similar in the wild. If we can’t interpret an alien logic running on silicon that we built, how will we interpret one from a civilization we’ve never met?
In this sense, AI becomes a rehearsal space: a quasi-alien mind we can query, constrain, and force into our universal semantic framework. The better we get at that, the better prepared we are for genuinely alien semiotic systems.
A Different Way to “Listen”
Traditional SETI listens for unusual signals. A USRS-informed SETI would also listen for unusual structures of meaning.
That doesn’t mean we stop building big antennas or clever filters. It means that when we see something that might be artificial, we bring to it a richer toolkit:
a catalog of core conceptual distinctions we expect any predictive intelligence to wrestle with;
a formal way of representing causal and temporal patterns abstractly;
and experience working with symbolic traces of non-human reasoning in AI systems.
Instead of asking only, “Is this signal non-natural?”, we can also ask, “Does this pattern behave like a mind talking to itself?”
That’s a much stranger, and in some ways more demanding, question. But it may be closer to what real contact would require.
Why Bother?
It is entirely possible that we will never receive an unmistakable interstellar message. The universe doesn't owe us a conversation.
But projects like USRS have value even if the sky stays quiet. They push us to examine our own assumptions about language, thought, and meaning. They force us to separate what is accidental about human communication—sounds, scripts, idioms—from what might be universal: events, causes, agency, time, value.
In the process, we get tools that help in other domains:
clearer ways to think about how AI reasons,
shared conceptual frameworks across human languages and cultures,
and perhaps a more rigorous vocabulary for that perennial philosophical question: what is a mind?
If some distant civilization is out there encoding its understanding of the cosmos into patterns we have yet to notice, we may or may not ever find them. But if we do, we will need more than sensitive instruments. We will need ways of thinking about meaning that reach beyond English, beyond Earth, and perhaps even beyond biology.
USRS is one speculative attempt at such a framework: a kind of semantic scaffolding that humans and machines can both inhabit. Whether or not anyone else is listening, it invites us to practice a more universal way of understanding—and to ask, in a disciplined way:
What would it mean to think so that another mind, somewhere in the universe, could in principle understand us?
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