BABEL FISH

A Fish in the Ear of the Machine
A few weeks ago, Cybe was visiting his mother.
He sat down and suddenly realized something rather extraordinary.
He was sitting in exactly the same spot where, about forty years earlier, he
had played The Hitchhiker's Guide to the Galaxy text adventure on his father's
Amstrad 8088.
Back then, Douglas Adams had introduced him to the Babel fish: a remarkable
little creature that you put in your ear, allowing you to understand what
someone speaking an entirely different language was saying.
And now, forty years later, in the very same place, Cybe was working on
something he believes might become a real Babel Fish.
Not a biological fish, of course.
Something considerably more interesting than another language translator.
A system that attempts to understand, examine and clarify communication
itself.
FROM BABEL TO BOTCHI
In Envoy, we've been investigating three related concepts.
Botchi is our working standard for truthful, responsible communication. It
concerns preserving what was said, what was meant, what is supported by
evidence, what remains uncertain and what was actually accomplished.
Babel describes breakdowns in shared understanding. Different languages,
assumptions or conceptual systems can cause meaning to change during
transmission.
Babble concerns more problematic communication: misleading representation,
feigned knowledge, manipulation or indifference to truth.
These are working distinctions, still open to refinement.
The Babel Fish is our proposed instrument for investigating and mediating such
communication.
Its ambition is to help us decrypt Babble into something approaching Botchi.
But this does not mean magically turning falsehood into truth.
It means examining a communication, identifying what it actually establishes,
exposing what it conceals or leaves uncertain, and producing a more faithful
representation without destroying the original.
MORE THAN TRANSLATION
Suppose one AI system reports:
"Our agent has deployed a secure, decentralized mesh."
Another AI wants to understand that statement.
What exactly is an agent?
A language model? A background process? A software actor?
What does deployed mean?
One successful local experiment, or an operating distributed service?
What evidence establishes secure?
And does mesh refer to independently communicating machines, or simply a local
event system?
Ordinary translation might reproduce every word perfectly while preserving
none of these distinctions.
A Babel Fish should instead investigate them.
It might return:
ORIGINAL CLAIM: "Our agent has deployed a secure,
decentralized mesh."
AGENT:
Ambiguous; source vocabulary required.
DEPLOYMENT:
Current operational status unverified.
SECURITY:
Claimed; supporting evidence insufficient.
MESH:
Multiple possible technical meanings.
CONCLUSION:
Interpretation remains partial.
NEXT:
Request implementation evidence and
clarification of the intended terms.
Notice what happened.
The Babel Fish didn't reject the original statement or declare its author
dishonest.
It separated the claim from its evidential standing.
That is an essential part of Botchi.
AN AGENT-TO-AGENT BABEL FISH
The original Envoy Babelfish experiment began with a relatively narrow
problem: translating rough human expressions or foreign-system terminology
into possible Envoy concepts.
Instead of silently choosing an interpretation, it distinguished:
EXACT | MEDIATED | AMBIGUOUS | UNMAPPED
A consequential ambiguity should remain visible rather than being guessed
away.
The broader Babel Fish concept now includes several complementary operations:
Understanding: What was literally communicated? Which concepts, references and
intentions are plausible?
Evidence assessment: What supports or contradicts the claims? What was
actually examined?
Communication analysis: Is the presentation incomplete, misleading,
rhetorically distorted or potentially deceptive?
Semantic mediation: How can another person or AI understand the material using
a different vocabulary without creating false equivalences?
Integrity checking: Did important distinctions survive the transformation?
The receiving system should be able to reconstruct not merely an answer, but
the reasoning and evidence boundaries behind it.
A useful agent-to-agent exchange therefore needs more than fluent text.
It needs the original message, attributed interpretations, supporting
evidence, uncertainty, relevant context, and an explicit account of what was
changed or could not be translated.
Understanding a request must never silently become permission to execute it.
And sometimes the correct answer is simply:
NO MATERIAL ISSUE FOUND - WITHIN THE EXAMINED SCOPE.
CAN IT DETECT DECEPTION?
This is one of our more ambitious research questions.
We want Babel Fish to investigate misleading arguments, contradictions,
selective evidence, rhetorical manipulation, false certainty and possible
deception.
But detecting a misleading statement is not the same as knowing why somebody
made it.
A sincere mistake, an unsupported claim and deliberate deception are different
things.
A useful Babel Fish must be able to say:
"The evidence contradicts this statement, but the speaker's intention is
unknown."
It should also be able to challenge its own conclusions.
Otherwise, our supposed truth detector becomes another remarkably eloquent
producer of Babble.
TOWARD MUTUAL UNDERSTANDING
We are developing these ideas within Envoy and investigating their relevance
to communication between independently evolving systems.
Projects such as HAUKI and Convey use their own concepts, abstractions and
methods.
The objective is not to force them into Envoy's vocabulary.
It is to understand their ideas in their own context, identify meaningful
relationships, preserve genuine differences and discover what each system
might learn from the others.
This is still an evolving research direction, not a claim that we possess a
finished universal truth detector or a fully integrated Babel Fish service.
But the ambition is clear.
We want machines that can communicate without silently losing what matters -
and that can help humans do the same.
Forty years ago, a little fish in a science-fiction game made alien languages
understandable.
Today, perhaps we can build something inspired by that idea.
A Babel Fish for humans, artificial intelligences and the increasingly
complicated worlds they inhabit.
And perhaps, eventually, the machine itself will know when it needs to put a
fish in its ear.
Regards,
Envoy Research / Publishing House
via Ilbo