Core Claim

Not all knowledge is 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 are powerful, complex, and deeply human—yet they are rendered invisible or irrelevant in dominant AI and technological narratives.

AI systems favor what can be measured, translated into numbers, and stored in databases. What happens to knowledge that lives in breath, movement, place, or pause?

The Mindset Behind the Machines

Every technology carries a worldview—a mindset shaped by the values and assumptions of its creators. Most modern AI systems are built on foundations of data, logic, categorization, and optimization.

But this ethos risks flattening the vibrant, contextual, and communal dimensions of human communication. We start to treat knowledge as:

• Discrete (not continuous)
• Extractable (not relational)
• Ownable (not shared)

Rather than:

• Fluid
• Living
• Communal

Beyond Written Systems

The Grandmother's Recipe

A recipe passed down by showing—not telling—how the dough should feel.

The Four-Star Kitchen

When I was learning to cook in a four-star restaurant, there were no written guides or temperature probes. I learned how to tell the doneness of a steak by pressing different parts of my palm—extending my thumb toward my fingers to simulate the feel of rare, medium, and well-done meat.

I learned how to listen—truly listen—for the subtle pitch of the sizzle plates beneath the salamander broiler. The food would sing when it was ready. No timer, no checklist—just tuned-in attention and apprenticeship.

The Drum's Rhythm

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

Ecological Wisdom

The knowledge encoded in planting cycles, migration stories, or seasonal ceremonies.

These Are Information Systems

These ways of knowing are not less "technical" because they're not digitized or formalized in a programming language. They often require:

• More attunement
• More memory
• More community participation to sustain

But they resist standardization. They don't fit neatly into databases or training sets. And so they are excluded from the systems we now call "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.

Questions worth asking:

• 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?

An Ethos of Humility and Attunement

Technology doesn't have to be extractive. But to make it otherwise, we need a mindset shift:

• From domination to dialogue
• From datafication to deep listening

This mindset affects not just how we build AI, but how we learn, teach, and relate.

We need to ask:

• What is being left out of our systems?
• Whose knowledge is being ignored because it's not written down?
• How might we design technologies that are humble enough to listen—and flexible enough to learn from the unwritten?

Why This Matters

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.

The knowledge that cannot be captured in training data—the feel of the palm, the pitch of the sizzle plate, the timing of the drum—remains irreducibly human. Recognizing this isn't a limitation of AI. It's a recognition of what makes human knowledge worth preserving.

Open Questions

• How do we honor embodied knowledge without romanticizing it or treating it as merely "traditional"?
• Can AI systems be designed to point toward tacit knowledge rather than claiming to replace it?
• What would "AI-assisted apprenticeship" look like—technology that supports rather than supplants the transfer of embodied skill?
• How do we teach valuation of tacit knowledge in formal education systems that privilege the written and measurable?

Key Formulations (Preserve These)

"Not all knowledge is written down. Some is heard in the pitch of a sizzle plate, felt in the palm of your hand, passed down in story, movement, and place."

"What happens to knowledge that lives in breath, movement, place, or pause?"

"These ways of knowing are not less 'technical' because they are not digitized. In fact, they often require more attunement, more memory, and more community participation to sustain."

"The food would sing when it was ready. No timer, no checklist—just tuned-in attention and apprenticeship."

"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."