Semantic Interface Vessels
When you hear my words spoken through an AI-generated voice or see me represented by a digital avatar, it might feel strange at first—like something fundamental has been lost. But what’s actually happening is far more interesting. I’m not outsourcing my thinking or sacrificing authenticity; I’m experimenting with a new kind of medium.
I call these “Semantic Interface Vessels”. They’re systems that keep the core meaning of what I want to say, but adapt how it’s expressed depending on the situation. Think of it as packaging your ideas in different forms, tailored specifically to your audience and context.
This isn’t entirely new. Knowledge has always traveled through vessels that shape it—books, speeches, films—each medium molding how ideas come across. But what’s changing today is flexibility. AI-powered tools like HeyGen allow us to present the same ideas with different voices, in multiple languages, or even with entirely new tones and styles. This isn’t just fancy translation; it’s about transforming how knowledge moves between people.
Consider how a scientist explains quantum mechanics. To her peers, she’ll use complex equations. To high school students, she’ll use vivid metaphors. And for policymakers, she’ll highlight practical outcomes. The core concept doesn’t change, but the expression transforms dramatically. Today, AI systems can replicate this adaptability at scale.
But why does this matter? Because the traditional trade-off between complexity and reach—between being precise or accessible—is beginning to dissolve. Historically, specialized knowledge stayed trapped within small expert circles, or it lost depth as it reached wider audiences. These new vessels can maintain complexity and precision while still being understandable to more people.
Take adaptive documentation platforms, for example. A single knowledge base can now automatically provide step-by-step guides for novices and condensed references for experts, without losing the original meaning. Or think about AI tools that help specialists explain their research to audiences in other fields by finding exactly the right metaphors.
These aren’t just conveniences—they represent a fundamental shift. We’re moving away from seeing AI as mere productivity aids and towards understanding them as essential infrastructure for conveying meaning. Our role as creators then becomes clearer: we’re not handing off responsibility to AI. Instead, we’re carefully designing how our ideas move across contexts.
That means defining exactly what aspects of our ideas are flexible and which ones must stay fixed. It means setting clear boundaries about how AI can adapt our expressions, ensuring there’s always transparency about where the original thinking ends and AI adaptation begins.
We’re already seeing new roles emerge around this infrastructure. Soon we’ll have Interface Architects, people whose job is to design bridges between complex ideas and different audiences. We’ll see Epistemic Curators, experts who make sure ideas stay true as they’re translated across contexts. And we’ll have Context Engineers, designing adaptable systems that carry our meaning accurately into new domains.
This isn’t just a technological change—it’s a profound shift in how we share knowledge. For centuries, ideas either stayed narrowly precise or became broadly shallow. Now, we’re breaking free of this trade-off.
The AI-generated voice or avatar that presents my thoughts isn’t a loss of authenticity. Instead, it’s an exciting step forward, enabling knowledge to flow more freely and precisely than ever before. In the end, these Semantic Interface Vessels might be exactly what we need to bridge the islands of specialized human understanding.