I've spent considerable time studying pedagogical approaches—how to explain complex topics, manage cognitive load, break down intricate systems into digestible pieces. The conventional wisdom suggests that complexity itself is the barrier: if only we could explain things more clearly, simplify the diagrams, polish the analogies, people would engage with difficult ideas.
But I've come to realize we're solving the wrong problem.
The real challenge isn't complexity. It isn't even the prerequisite knowledge or the time investment required to build mental models of sophisticated systems. The fundamental barrier is far more prosaic and far more intractable: we're fighting for attention in an ecosystem that has none left to give.
The Scarcity Economy
We live in an era of informational abundance that has created a scarcity economy of attention. Every hour brings another flood of signals, notifications, updates, and demands for cognitive engagement. Our information diet has become so calorically dense, so hyper-optimized for immediate consumption, that anything requiring more than ten minutes of sustained focus feels like an unreasonable ask.
This isn't a moral failing. It's an adaptation to an environment that has fundamentally changed faster than our cognitive architecture can evolve. When your day is parceled into dozens of context switches, when every idle moment is immediately filled with algorithmically-optimized content, the mental overhead of engaging with something genuinely complex becomes prohibitive.
The irony is bitter: we have unprecedented access to information and unprecedented tools for explaining it, yet we're less capable than ever of engaging with ideas that don't provide immediate utility or dopamine hits.
The R&D Dilemma
This creates a particularly acute problem for research and development work. Innovation—real innovation, not incremental product improvements—operates on fundamentally different timescales than our attention economy allows.
R&D is inherently:
High-context: Understanding the work requires substantial background knowledge
Delayed gratification: Results emerge over months or years, not minutes
Uncertain: The path isn't clear, and failure is common
Nuanced: The devil is truly in the details
None of these characteristics map well to TikTok videos, viral tweets, or even well-designed slide decks. You cannot adequately explain decision traces in causality AI with dancing cats, no matter how charming those cats might be. Probability models and their implications don't lend themselves to 60-second explainers featuring attractive hosts.
This isn't to say that good communication doesn't matter—it absolutely does. But even the most skilled communicator faces an uphill battle when the audience's attention budget has already been exhausted before they even arrive.
The Magic Problem
There's a second, subtler challenge that compounds the attention deficit: explanation destroys magic.
When you truly explain how something works—when you open the hood and show the gears, the tradeoffs, the limitations—you inevitably diminish the sense of possibility that makes innovation exciting. The deep dive reveals not just the elegant solutions but also the ugly hacks, the unsolved problems, the fundamental constraints.
Marketing thrives on magic. It sells vision, potential, the promise of transformation. But rigorous explanation requires honesty about what doesn't work, what can't work, what will take years to work. It's much harder to generate enthusiasm for "this approach shows promise in specific constrained domains but faces significant scalability challenges" than for "AI will revolutionize everything."
The more thoroughly you explain your innovation, the more you reveal its current limitations. The more transparent you are about the research process, the less certain everything becomes. This honesty is intellectually necessary but commercially disadvantageous.
The Structural Bind
This creates a structural bind for anyone doing serious R&D work who also needs to communicate it:
If you simplify aggressively, you can capture attention but may misrepresent the work, oversell capabilities, and contribute to the hype cycle that ultimately damages credibility.
If you explain thoroughly, you lose most of your potential audience before you finish the introduction, and those who remain are left with a realistic but decidedly un-magical understanding of what's actually possible.
Neither option is satisfying. The first feels dishonest; the second feels futile.
What This Means for Innovation
The attention deficit creates several concerning dynamics for innovation ecosystems:
Selection pressure favors the easily digestible over the genuinely novel. Ideas that can be grasped in minutes will always outcompete those requiring hours, regardless of their respective merits.
High-context work becomes increasingly isolated. When the barrier to entry for understanding what you're doing is significant, you end up talking primarily to a small circle of specialists—which can be intellectually productive but limits broader impact and support.
The funding follows the buzz. Investment capital, whether venture funding or research grants, gravitates toward work that can be explained in a pitch deck. Complex, foundational research that resists simple narratives struggles to compete.
Innovation theater displaces actual innovation. There's enormous pressure to focus on the presentation, the demo, the vision deck rather than the unglamorous work of actually solving hard problems.
No Easy Answers
I don't have a solution to this problem. Exhorting people to "just focus more" ignores the structural realities of how attention economics actually work. Suggesting that researchers just need better communication skills misses the fundamental mismatch between what R&D requires and what our information environment supports.
What I do know is this: we need to acknowledge the problem explicitly. The challenge isn't just explaining complex work better—it's finding ways to create space for sustained attention in an environment actively hostile to it. It's navigating the tension between honest communication and effective advocacy. It's recognizing that some ideas simply cannot be compressed into the formats our current ecosystem rewards.
Perhaps the first step is just admitting that the emperor has no clothes: we're trying to do slow, complex, nuanced work in a fast, simple, declarative world. And increasingly, the world is winning.
The question that haunts me: what innovations are we missing because they require eleven minutes of attention in a world that only gives ten?