The Unwritten Code

Rethinking AI and Technology Through Hidden Ways of Knowing

In the rush to digitize everything — from our classrooms and communication to our art and identities — we often forget that not all systems of knowledge are written down. Much of what humans know, create, and pass down is embedded in gesture, rhythm, ritual, oral storytelling, and environmental cues. These systems of meaning and communication are powerful, complex, and deeply human — yet they are often rendered invisible or irrelevant in dominant technological narratives.

This matters deeply as we enter a world increasingly shaped by artificial intelligence.

The Mindset Behind the Machines

Every technology carries with it a worldview — a mindset or ethos shaped by the values, assumptions, and cultural contexts of its creators. Most modern AI systems are built upon foundations of data, logic, categorization, and optimization. They favor what can be measured, translated into numbers, and stored in databases.

But what happens to knowledge that lives in breath, movement, place, or pause?

What happens to ways of knowing that are relational rather than transactional?

The ethos behind much of today’s AI and information systems risks flattening the vibrant, contextual, and communal dimensions of human communication. We start to treat knowledge as discrete, extractable, and ownable — rather than fluid, living, and shared.

Beyond Written Systems

Think of a grandmother’s recipe, passed down by showing — not telling — how the dough should feel.

Or the rhythm of a drum that signals danger, celebration, or history in a community.

Or the ecological wisdom encoded in planting cycles, migration stories, or seasonal ceremonies.

These are rich information systems. They are not less “technical” because they are not digitized or formalized in a programming language. In fact, they often require more attunement, more memory, and more community participation to sustain.

But they resist standardization. They don't fit neatly into databases or training sets. And so they are often excluded from the systems we are now calling “intelligent.”

Rethinking AI with Broader Epistemologies

If we’re serious about building ethical, inclusive technologies — we need to expand our sense of what counts as intelligence and who gets to define it. That means recognizing and honoring the unwritten, the embodied, the communal, and the ancestral.

This isn’t just a matter of fairness. It’s a creative opportunity.

What might AI look like if it were designed with oral tradition in mind?

What kinds of machine learning models would emerge from a different theory of language — one that centers rhythm, story, or silence as core data?

How might design change if we took seriously the knowledge held in communities who have long communicated outside of print — and outside of dominant Western frameworks?

Toward an Ethos of Humility and Attunement

Technology doesn’t have to be extractive. But to make it otherwise, we need a mindset shift — one that moves from domination to dialogue, from datafication to deep listening.

This mindset doesn’t just affect how we build AI. It reshapes how we learn, teach, and relate.

We need to ask:

In the end, the most powerful intelligence may not come from bigger models or faster chips, but from our ability to imagine technologies that serve life in all its diverse, embodied, and unscripted forms.