There is something almost pathological about the way we talk about science these days. Open any science communication platform and you’ll encounter the same ritualistic performance: an enthusiastic presenter, standing before elegantly rendered animations, breathlessly explaining why gallium arsenide semiconductors should capture your imagination. The production values are pristine, the information accurate, but something essential has gone missing. That spark which transforms mere data into genuine fascination—the thing that makes someone stop mid-scroll and think, “I must understand this”—rarely materializes.

Watch enough of these videos and a peculiar pattern emerges. The creators seem to believe that science sells itself, that the intrinsic elegance of quantum mechanics or the practical implications of CRISPR will shine through any competent explanation and convert the uninitiated. It’s a touching faith, but one that ignores a fundamental truth: beauty without context is merely aesthetics, and facts without motivation are simply trivia.

The problem runs deeper than production techniques or pedagogical approaches. Science, for all its power to illuminate the workings of the universe, cannot seem to construct a compelling narrative about its own value. We have become experts at summarizing our discoveries but terrible at conveying why those discoveries might matter to anyone beyond our immediate professional circles.

This failure reflects a fundamental mismatch between the nature of scientific work and the structure of human attention. Science advances through incremental insights, methodical observation, and the gradual accumulation of evidence—a process that unfolds over months, years, sometimes decades.

**doesn’t explain why stories are thing that become intrinsically interesting. (Though I think stories have evolved with humans, and we’re almost generically tuned to listen to monomythic strucutres)

Stories, by contrast, require protagonists with intelligible motivations, obstacles to overcome, and stakes that feel immediate and personal. The patient pursuit of knowledge does not naturally conform to narrative expectations.

Consider the challenge facing anyone trying to make, say, lattice-based cryptography accessible to general audiences. The conventional approach starts with technical fundamentals—mathematical structures, computational complexity, algorithmic approaches—and works outward toward potential applications. But this sequence misses the essential preliminary question: why should anyone care? Without a compelling answer, all the sophisticated explanations in the world amount to elaborate intellectual tourism.

The storytelling problem becomes acute when we examine what makes other domains naturally engaging. Financial markets provide built-in drama: clear winners and losers, immediate consequences, the perpetual tension between risk and reward. Sports offer ready-made protagonists, identifiable adversaries, and outcomes that matter viscerally to participants and spectators alike. Even mundane activities like cooking can be structured as transformation narratives with visible before-and-after states.

Science lacks these convenient narrative scaffolds. The researchers are often more invested in technical challenges than in personalities. The timescales are wrong—years or decades typically separate initial insights from practical applications. The stakes, while potentially enormous, feel abstract and temporally distant. Most problematically, the work itself is designed to eliminate the kind of subjective interpretation and emotional investment that creates compelling characters.

This creates what I’ve started calling the “antagonist problem.” Every engaging story requires opposition—something to struggle against, outwit, or overcome. But what serves as the villain in scientific narratives? Ignorance feels too abstract. Funding constraints are bureaucratic rather than dramatic. The laws of nature themselves are not malevolent, merely indifferent. Without clear opposition, scientific stories default to vague gestures toward “expanding human knowledge” or “addressing humanity’s greatest challenges.”

The result is content that feels educational rather than transformative. Audiences absorb information about quantum computing or genetic engineering or climate modeling, but they don’t develop the personal investment that sustains genuine engagement. The facts pass through consciousness without altering how people understand themselves or their relationship to the world.

This matters more than it might initially appear. In democratic societies, public understanding of science influences everything from research funding priorities to regulatory frameworks to individual decisions about health and technology. When scientific communication fails to generate authentic engagement, we end up with populations that are simultaneously dependent on scientific advances and alienated from scientific thinking.

The standard response is to intensify accessibility efforts—simpler explanations, more polished visuals, increasingly entertaining formats. But accessibility alone cannot solve the engagement problem. You can make quantum mechanics as straightforward as possible, and it will still feel irrelevant to someone deciding how to spend their Tuesday evening. The first issue is connection, not comprehension.

I say first, because I see ‘getting someone interested enough to pay attention’ as just a first step. It’s the foundational step in a certain hierarchy of understanding the progression through which genuine intellectual curiosity develops. At the bottom lies apathy, the default state toward most topics for most people. Above that sits curiosity, sparked by glimpsing something beautiful, mysterious, or personally relevant. Higher up is the desire to operate on the same cognitive plane as admired figures, mastering their vocabulary and conceptual frameworks. At the apex lies true competence and the drive to apply insights creatively.

Most science communication targets the middle of this hierarchy, providing information to audiences who already possess some motivation to learn. But it systematically fails to create that motivation in the first place. It cannot answer the foundational question that precedes all others: why should this matter to me, personally, right now?

The entertainment industry grasps this intuitively, but science fiction has shown us glimpses of how this might work. Stories that put scientific problem-solving at their center—where characters must think systematically to survive, where technical competence becomes heroic—demonstrate that audiences can be drawn to scientific thinking when it’s embedded in compelling human drama. The key is making the science integral to the story rather than decorative.

This suggests a different approach to the engagement problem. Rather than trying to make abstract scientific concepts inherently compelling, we might focus on making scientific thinkers compelling—and then let curiosity about their methods follow naturally. People learn about things because they want to be like the people who do those things. The young basketball player doesn’t study Michael Jordan’s shot mechanics out of abstract interest in biomechanics; he studies them because he wants to be Michael Jordan.

This is where the concept of mimetic desire becomes crucial. René Girard observed that we don’t want things independently—we want them because other people want them, because other people make them seem desirable. Our desires are mediated through models, people who show us what’s worth wanting. And what we actually want is not the object itself but the quality of being that our models seem to possess.

The learning hierarchy operates through this mimetic mechanism more than through instruction. At the base level, apathy gives way to curiosity when we glimpse someone whose competence makes them seem formidable, creative, or mysteriously capable. We don’t develop interest in quantum computing because someone explains superposition clearly—we develop interest because we see someone whose mastery of quantum computing makes them appear to possess something we lack. Their mastery of quantum computing makes them seem formidable, creative, or mysteriously capable. We watch a burgeoning protagonist face trials and tribulations.

This is where most science communication fails catastrophically. It presents information divorced from the people who discovered it, developed it, or use it daily. We get explanations of CRISPR gene editing without meeting the researchers who spend their days designing guide RNAs. We learn about machine learning algorithms without encountering the graduate students who debug training loops at 3 AM.

The work becomes abstract, disconnected from the human drama of actually doing science. But simply putting scientists on camera won’t solve this problem. There’s a deeper issue with protagonist selection that most science communication gets wrong.

The problem is what I call the “Chris Traeger effect”—named after the relentlessly positive Parks and Recreation character whose enthusiasm for everything feels simultaneously genuine and deeply unsettling. When scientists become too excited about their work on camera, when their passion seems to overwhelm their judgment, audiences don’t want to identify with them. They want to learn from people who seem fundamentally like themselves, not from people who appear to have crossed some threshold into obsessive weirdness.

This creates an impedance mismatch between the scientist’s authentic enthusiasm and the audience’s need for relatable protagonists. The grad student who has spent three years building a better photon detector may genuinely care about single-photon detection with an intensity that approaches the mystical, but that intensity, however authentic, can make her seem like someone the audience wouldn’t want to become.

We’re beginning to see more scientists take on influencer roles, trying to bridge this gap with varying degrees of success. The quality of such content depends heavily on whether the scientist can come across as likeable rather than merely passionate—a much rarer skill than technical competence. The ones who succeed tend to be those who can modulate their enthusiasm, who remember what it felt like not to care about their subject matter.

This suggests that the learning hierarchy requires different approaches at different levels. Content designed to move people from apathy to initial interest needs to be highly structured and story-like, but it often shouldn’t have the knowledgeable scientist as the protagonist. Scientists already know the answers, and unless their knowledge is going to be tested in dramatic ways, they aren’t inherently interesting to watch.

Consider an alternative approach: a science communicator dropped into a research environment with a specific, high-stakes challenge. “You have three months to understand this lab’s work well enough to explain it to a congressional funding committee, or the research program gets cancelled.” Now we have a compelling setup—a protagonist the audience can identify with, facing a genuine challenge that requires learning complex material under pressure.

This protagonist doesn’t need to be relentlessly enthusiastic about quantum mechanics or protein folding. They need to be competent, curious, and recognizably human. The audience can follow their journey from confusion to understanding because it mirrors the journey the audience would take. The scientists in the lab become supporting characters—sources of knowledge and occasional frustration, but not the emotional center of the story.

The real antagonist becomes clear: not ignorance in the abstract, but the specific challenge of mastering difficult material when the stakes are real. Will our protagonist be able to distinguish between the crucial insights and the technical minutiae? Can they find ways to make complex ideas accessible without sacrificing accuracy? Will they understand the work deeply enough to defend it against informed skeptics?

These are genuinely dramatic questions, and they put scientific content at the center of a story structure that audiences already understand. The science isn’t decoration—it’s the obstacle the protagonist must overcome. But the protagonist isn’t someone who already loves this material; they’re someone learning to appreciate it under pressure.

This approach works particularly well for moving people up from the bottom of the learning hierarchy. Once someone has developed initial interest, once they’ve moved past apathy toward curiosity, then you can introduce them to actual scientists expressing their genuine enthusiasm in their own words. But the foundation has to be laid first—the audience has to want to learn before they can benefit from encountering people who are passionate about teaching.

The mimetic desire mechanism works differently at different levels of the hierarchy. At the bottom, people need to see themselves in the protagonist—someone who starts out not knowing much but who grows visibly more competent over time. Higher up, they can begin to admire the deep expertise of researchers who have devoted their careers to specific problems.

We’re likely to see more graduate students and postdocs experimenting with influencer-style content, and this isn’t necessarily a bad development. But their effectiveness will depend on their ability to remember what it felt like to be confused by their subject matter, to reconstruct the path they took from ignorance to understanding. The best scientific influencers will be those who can make their enthusiasm feel earned rather than given.

The key insight is that different parts of the learning journey require different kinds of stories and different kinds of protagonists. Moving someone from apathy to interest requires carefully constructed narratives with relatable characters facing genuine challenges. Moving them from interest toward deeper understanding can rely more on direct encounters with passionate experts.

But we’ve been trying to use the second approach to accomplish the first goal, and wondering why it doesn’t work. A graduate student’s authentic excitement about her research is compelling to people who already care about science. To people who don’t, it can seem like evidence that scientists are a different species entirely—brilliant, perhaps, but not people you’d want to have a beer with.

Until we learn to construct stories that put scientific learning at the center of compelling human dramas—stories with protagonists audiences can actually identify with—we’ll continue inhabiting a world where the most consequential intellectual work remains invisible to those who fund it, depend on it, and must ultimately decide how it gets used. We’ll have scientific literacy without scientific appreciation, technical competence without public engagement, and breakthroughs that change everything understood by almost no one.