From the intricate dance of genes to the complex interplay of ecosystems, the life sciences are revealing that the nature of scientific truth might be more nuanced than we ever imagined.
What does it mean for science to be "true"? For centuries, this question has haunted philosophers studying physics and chemistry. But today, some of the most compelling answers are emerging from an unexpected source: biology.
This isn't just abstract philosophy—it's about understanding why biologists can passionately debate the same questions for decades without settling them, why a textbook diagram of a cell differs from an electron micrograph of that same cell, and how our very evolutionary history shapes how we perceive and understand the living world.
In physics, the debate about realism often revolves around whether electrons "really exist" or are merely useful fictions. Biology presents a different challenge altogether. The problem isn't whether organisms exist—clearly they do—but whether our scientific explanations capture their true nature, given biology's historical complexity and mind-boggling diversity.
Long-standing debates about how often different biological processes actually operate in nature 3 . These controversies are rarely settled definitively; instead, scientists typically lose interest in the original question and move on.
As scientists argue about relative frequencies, they generate valuable modal knowledge—knowledge about what could possibly happen under specific circumstances, even if we never determine exactly how often it does happen 3 .
| Phenomenon | Alternative Explanations | Status |
|---|---|---|
| Evolution of extravagant sexual displays | Good genes indicators vs. arbitrary mate preferences | Ongoing |
| Formation of new species | Geographic isolation vs. non-geographic barriers | Periodically revisited |
| Fixation of traits in populations | Natural selection vs. genetic drift | Continually debated |
Perhaps the most profound challenge biology poses to traditional realism comes from evolutionary theory itself. If our cognitive capacities are the products of natural selection, then our minds were shaped for survival and reproduction, not for dispassionate contemplation of ultimate reality.
The abstract philosophical concept of reality as it exists independently of any observer.
The environment in which we must find food, avoid predators, and raise offspring—what actually matters for survival 1 .
Our scientific theories work not because they perfectly mirror nature, but because they help us successfully operate within it—a view that aligns with what philosophers call "perspectivalism" 4 .
Nowhere is the realism debate in biology more heated than in discussions of biological functions. When we say "the function of the heart is to pump blood," what do we really mean?
Argues that functions are real biological properties. The most prominent version, the etiological theory, holds that a trait's function is whatever it was naturally selected for.
Maintains that functions are real but relative to our explanatory interests. Whether a trait has a function depends on the perspective of the researchers studying it.
Claims that organisms don't really have functions any more than they have bodily humors or mystical life forces. Function talk is at best a convenient fiction.
This seemingly straightforward statement contains what philosophers call teleology—the idea that effects (pumping blood) can explain the existence of their causes (hearts) 4 . This creates a puzzle: how can a future benefit explain why something exists in the present?
The question of biological realism isn't just for philosophers—it directly influences how scientists communicate their findings and how the public understands biology. A 2022 study investigated how people perceive realism in biological images, with fascinating implications for science communication 5 .
Researchers systematically varied three visual properties—shading, color, and surface texture—in images of biological structures like cells and viruses. Participants were shown pairs of images and asked which they perceived as more realistic, which they preferred, and which made them want to learn more.
| Visual Property | Impact on Realism Perception | Impact on Exploration Desire |
|---|---|---|
| Shading | Significant predictor of perceived realism | Significant predictor of desire to explore |
| Color | Significant predictor of perceived realism | Less significant than shading |
| Surface Texture | Significant predictor of perceived realism | Not a major predictor |
| Image Type | % Judged Most Realistic | % Prompting Exploration |
|---|---|---|
| High shading + Full color | 68% | 72% |
| High shading + Limited color | 59% | 64% |
| Low shading + Full color | 47% | 51% |
| Low shading + Limited color | 31% | 29% |
The researchers interpreted these findings through construal level theory—the idea that realistic portrayals make distant or abstract concepts feel psychologically closer and more concrete, thereby motivating engagement 5 .
The results showed that all three visual properties significantly predicted whether participants viewed images as realistic 5 . More importantly, images perceived as more realistic also generated greater desire for further exploration.
How do biologists navigate these complex philosophical waters while doing actual research? Several conceptual tools help manage biology's unique challenges:
Instead of focusing exclusively on what actually happens, biologists increasingly study what could happen under different conditions. This shift from actuality to possibility has proven particularly fruitful in evolutionary biology 3 .
Rather than seeking one "true" model, biologists often maintain multiple competing models in what some philosophers call a "toolkit view of biological theory" 3 . Different models serve different explanatory purposes, and their usefulness varies by context.
Biological processes operate differently across scales. As one review notes, "influences of abiotic and biotic processes on species distributions vary across grains and extents" 6 . Sophisticated models must account for these scale dependencies to achieve predictive power.
Modern biology recognizes that development is "a life-long, environment-dependent process" 7 . This requires studying how environmental influences at different life stages interact, rather than focusing solely on early developmental periods.
Biology may not give us the simple, law-based truths that physics once promised, but it offers something perhaps more valuable: a nuanced understanding of knowledge as a tool for navigating a complex, historically contingent, and multi-leveled living world.
The compelling conclusion emerging from contemporary biology is that realism and usefulness are not opposed—they're deeply intertwined. Our biological knowledge is realistic precisely because it's useful for our specific needs and capabilities as evolved organisms with particular perceptual and cognitive constraints.
As biology continues to reveal life's breathtaking complexity, it also reshapes our understanding of scientific knowledge itself—not as a perfect mirror of nature, but as an evolving, multifaceted, and endlessly fascinating dialogue between the knower and the known.