As artificial intelligence (AI) becomes increasingly embedded in society, it's essential to pause and reflect on the foundations that sustain it—and the dimensions to which it extends. At the heart of AI's learning are datasets, whose structure and content shape how these systems interpret and respond to the world. This reliance creates a deep interdependence—one that not only informs AI's capabilities but also defines its potential blind spots. In light of this, we must ask: What forms of understanding might this process exclude, especially those not easily captured in digital form?
Indigenous wisdom, passed down orally or embedded in daily practices, conveys a deep connection to place and history. Vernacular construction technologies, local materials, and ways of inhabiting—rooted in specific conditions—embody a collective memory and intelligence that algorithms may struggle to grasp fully in their cultural and material depth. Are we capturing this material memory? And if so, what might still be missing or diluted in translation? Organizations such as UNESCO have raised questions around AI, especially in the context of increasing digitization of content on the Internet, which brings to the forefront the complex and often tenuous intersection with traditional knowledge systems.
The gap between technology and the vernacular was evident not so long ago. Today, with the rapid acceleration driven by AI, that gap persists—and may even be widening. While innovation moves in one direction, local materials and vernacular techniques lie on the other side, generating an increasingly marked disparity. It's true that generative AIs can recognize visual patterns and accurately replicate the fractal designs of the Kassena tribe or the self-supporting tents of Mongol nomads. But can it truly understand the techniques or narratives behind them?
Collective Intelligence and the Contextual Understanding of Building Materials
When comparing "modern" materials with vernacular ones, a fundamental difference emerges in how knowledge is transmitted. AI can easily process modern materials—quantified in data, yields, and imagery—while traditional materials rely on knowledge passed through practice and shared experience.
In vernacular cultures, people understand materials in a deep and situated context: climate, harvest time, thermal behaviors, accessibility, and symbolism. They are not just objects of construction, but living elements within a shared ecosystem. This form of knowledge moves away from systematization. It is nourished by direct experience, rooted in everyday life, in what we call a collective intelligence that emerges from the constant interaction of the community with its environment.
We can also consider what Juhani Pallasmaa reflects on traditional African cultures in an interview, where building practices are transmitted more through the haptic sense than visual codes or styles. Rather than being defined by abstract or aesthetic concepts, the teachings pass through sensation, touching, feeling, and experiencing the materials. Thus, we understand that the téchne—art, craft, skill—and logía—study, knowledge—are not limited to plans, data, and technical specifications, but are expressed in direct contact with the environment: a palpable knowledge, inherited across generations, a collective wisdom transmitted not only rationally, but from body to body, from generation to generation.
Contemporary Technology as a Bridge Between the Natural and the Artificial
Rather than positioning artificial intelligence in opposition to vernacular traditions, it may be more productive to explore their points of convergence. Contemporary technology serves as a bridge. Depending on the perspective, people may see it either as a manifestation of the artificial or as a tool grounded in technique.
In this view, contemporary technologies provide new ways of engaging with vernacular knowledge—through documentation, analysis, and even production. Applications such as LiDAR (Light Detection and Ranging) scanning allow for high-precision 3D mapping and digitization of space. This technology is beneficial for preserving and studying constructions, generating detailed digital models that provide valuable data for analysis. A related technique is photogrammetry, which allows the creation of three-dimensional models from images through photographs and software. This measurement and modeling technology helps document and reproduce construction techniques digitally. The data collected by these technologies can intersect with artificial intelligence to predict materials' durability, behavior, or adaptability under changing conditions, thus offering options to optimize their use.
But documentation is only one part of this convergence. To translate this integration to the physical plane, technologies such as digital fabrication have been key in linking materials and technological systems. Additive methods—such as 3D printing with earth-based materials—make it possible to recreate complex forms that would be difficult to achieve manually with traditional labor. These technologies open up the possibility of creating prototypes or architectural components based on vernacular techniques, adapting them to new needs.
Throughout this process —whether scanning, documenting, or fabricating/printing— it is essential to continually ask: Why? This questioning sustains critical reflection. For contemporary architectural production to incorporate contextualized construction techniques, it must go through an understanding of the climate, the link with the territory, and, why not, even community life. Only in this way can they be considered a form of living heritage. Without these elements, an earth block is nothing more than a collection of minerals compressed in a mold.
This type of knowledge may not be fully transferable to a digital environment, nor may it need to be fully "understood" by artificial intelligence. What matters most is that we, as human beings, recognize the value each of these elements brings to the construction of our environment. It is often said that knowledge of the past offers valuable guidance in the face of environmental degradation, the climate crisis, and other pressing issues. In light of this, it is pertinent to rethink the notion of "intelligence" as the capacity to adapt to the environment, from a perspective interconnected with different disciplines and forms of knowledge.
This article is part of the ArchDaily Topics: What Is Future Intelligence?, proudly presented by Gendo, an AI co-pilot for Architects.
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