Present Archaeology – The Eternal Past of the Spotless Mind
Dragons unevenly distributed.
(This is the second in my series on Present Archaeology. I recommend reading the first, The Present Problem, before diving into this one.)
Present Archaeology, as I explored in the first essay, excavates the unknown unknowns hiding in our current moment. Reader feedback centered on Žižek's "unknown knowns"—a perspective that reframes the entire structure. In my mind, and contrary to established narrative, these aren't a fourth dimension of the Rumsfeld matrix; they're replacing unknown unknowns entirely. We're constructing a reality where the very possibility of not-knowing is being erased. But Present Archaeology isn't just about finding what's hidden—it's a mental model for maintaining mystery in the face of systems designed to eliminate it. It's the practice of asking different questions, especially when every tool promises comprehensive answers.
This erasure has been decades in the making. We've been building Borges' Library of Babel (shout out to Martin Spindler for reminding me of this) for decades. First through the internet's infinite pages, now through AI's endless responses. The library contains everything that could ever be written, making true discovery impossible because everything already exists somewhere in the stacks. Similar to Joel in "Eternal Sunshine of the Spotless Mind," we've collectively chosen to erase not our memories, but our capacity to imagine what might exist beyond the catalog. The future becomes impossible because there's nothing left to find.
Yet humans once had tools for preserving the unknowable. Medieval cartographers wrote "Here be dragons" at the edges of the known world. These three words acknowledged that the category of the unknowable existed. Interestingly, their dragons were often composites of real creatures sailors had glimpsed—attempts to make the unknowable knowable through imagination. Even then, they clearly marked where knowledge ended and speculation began. We've lost this crucial distinction.
AI promises to fill in all blank spaces. But what if we're creating a reality that feels like every question has already been answered., Or, to put it differently, in which there are no new questions. Are we are erasing mystery by making it unimaginable to us?
In conversation about this very topic, I found myself saying: "it's impossible to ask the machine something that it, supposedly, doesn't know." AI systems don't say "here be dragons." They generate plausible content that fills the void where we should be looking for dragons.
This is where Žižek's "unknown knowns"—things we know but don't know we know—comes in. The experience of AI makes everything feel like an "UNKNOWN KNOWN". Every insight, every discovery, every possibility seems to already exist in the latent space of the model. We experience exploration as remembering what the system already contains. And this experience shapes our imagination. Would we be able to recognize a genuine discovery anymore?
The implications are … stark. Traditional knowledge work assumes a progression from unknown unknowns to known knowns. But if AI makes everything an unknown known, we're trapped in an eternal past. The act of discovery becomes an act of retrieval. The future—as a space of genuine unknowability—disappears. This is where Present Archaeology becomes essential: it's the practice of recognizing that the present itself is the territory of mystery, not the future. While we fixate on what's ahead, the dragons live in the overwhelming complexity of now.
Consider strategic planning. Teams use AI to analyze markets, behavior, competition. The system returns comprehensive insights, beautifully structured. But these aren't discoveries—they're excavations of patterns already present in historical data. We mistake retrieval for revelation.
As Martin noted, we're experiencing "system overwhelm at a higher level because the indexing breaks down." We can't know anymore what we know, including our own tacit knowledge—those cultural patterns, unspoken rules, and inherited assumptions that shape organizations. These unknown knowns become visible only through encounter with the genuinely foreign. But if AI systems are trained on existing data, they reinforce rather than reveal these blind spots. The blank spaces on our maps don't get marked with dragons—they get filled with generated content that feels real enough to stop us from exploring.
Preserving space for dragons requires cultural intelligence—knowing when completeness is actually incompleteness, feeling confident enough to trust your instincts when something seems too neat, too comprehensive. But we've been systematically trained not to use this capacity. It's not that people lack taste or discernment. As W. David Marx notes, taste develops through "conscious desire to learn more" combined with accumulated experience. Like wine connoisseurs whose growing expertise makes them reject what once pleased them, developed judgment means knowing when the easy answer isn't the right answer. But this kind of discernment requires permission to acknowledge unknowability.
The human-in-the-loop only functions as a safeguard if that human feels permitted to say "here be dragons." But in efficiency-driven environments where AI promises comprehensive answers, who has the organizational capital to insist on preserving blank spaces? Present Archaeology provides this permission—it's the stance that values peripheral vision over focused retrieval, that asks not "what does the system know?" but "what questions aren't we asking?"
Bruce Sterling, who helped coin "design fiction," once said "the future is a kind of history that hasn't happened yet." We might now say: the present is a kind of future we haven't learned to see yet. The medieval cartographers understood this—their maps honestly admitted where knowledge ended. In our rush to fill every blank space, we're losing the capacity to imagine different futures. AI doesn't eliminate mystery; it makes ignoring mystery so convenient that we forget the unknowable surrounds us.
Present Archaeology is more than just excavation—it's a practice of staying present with overwhelming complexity. While AI promises to manage the infinite library by narrowing our focus to retrievable answers, Present Archaeology insists on peripheral vision. It's the mental model that keeps asking: what dragons are we missing while we're busy searching the catalog?
The spotless mind remembers everything perfectly. But perfect memory might be the enemy of discovery. In the eternal past of the spotless mind, all questions have answers—they're just waiting to be retrieved. The dragons aren't gone. We've just forgotten how to see them. Yet with Present Archaeology as practice, even our most comprehensive tools can become instruments of mystery. The difference lies not in the tool but in the questions we bring to it.
Present Archaeology series is exploring different themes at the intersection of knowledge, strategic work and mystery. It will explore different models, frameworks and concrete application examples. As noted in this essay, I both welcome and use feedback to evolve my own thinking. Please reach out with feedback, ideas or sources that I should consider in my thinking.