There’s not a lot going for uncertainty.

As Harvard professor emeritus of zoology and biology Richard Lewontin wrote in the preface to his book “Biology as Ideology: The Doctrine of DNA”, “a simple and dramatic theory that explains everything makes good press, good radio, good TV, and best-selling books.” Meanwhile, he noted, “if one's message is that things are complicated, uncertain, and messy, that no simple rule or force will explain the past and predict the future of human existence, there are rather fewer ways to get that message across.”

It makes sense that people aren’t necessarily comfortable with the idea of uncertainty. When you face uncertainty, there is more activity in emotion-related regions of your brain like the amygdala and anterior insular cortex, according to Harvard neuroscience professor Elizabeth Phelps. People can face ambiguity aversion, where they would choose to face known rather than unknown risks, even when the known risk may be a less optimal choice.

But as we strive to understand life’s complexities, uncertainty is inevitable in science. So let’s consider the dance between the two.

First, in regards to terminology, “uncertainty” in science isn’t not knowing but a measurement of how well something is known. For example, in climate science, uncertainties in global temperature rise refer to the margin of error, the degree of exactness in an experiment or theory or prediction. It’s about how hot the stove is, not whether or not the stove is on. Second, though science aims to remove unknowns about the world, it will always be a work in progress.

Ed Yong, science writer for The Atlantic, told me in an interview that “science is often mischaracterized as a procession of facts, whereas it really is much more of a meandering path towards less uncertainty.” Thus, it is crucial to emphasize that the scientific process is nebulous and dynamic, and that scientific conclusions that can change based on additional evidence.

“People might not be used to the idea. But I think that's because we as a field have often done our job badly. We've conditioned people to expect easy answers when the truth is usually much more complicated,” Yong said.

In many ways, it would be more painless to consider science as a series of proclamations climbing with each new discovery and data point. And in many ways, more information has decreased scientific uncertainty.

Harvard astrophysics professor Alyssa Goodman founded The Prediction Project, which analyzes how humans have made predictions from ancient civilizations to modern frameworks. In some ways, Goodman said, uncertainty has decreased substantially over time. Weather forecasting, for example, has become far more refined with modern data and technology.

But information and data aren’t necessarily proportional to certainty and predictive power. In the early 19th century, a French physicist wondered if we could predict everything. In a concept now known as Laplace’s Demon, he posited that if someone (the demon) knew the position and momentum of every particle in the universe, then the past and future states of those particles – and by extension, states of the universe – could be deterministically predicted.

“It turns out that quantum mechanics comes along and basically breaks that, as does chaos theory,” Goodman said in an interview. “There's just some element of randomness in them that you cannot get rid of.”

Sometimes, accumulating data might even bring a false sense of security to scientific advancement. Many even see big data as the key to decreasing uncertainty, though others are skeptical.

“Data collection is the easiest thing for the government to fund and the easiest thing for people to do,” Craig Venter, the synthetic biology pioneer known for his contributions to the Human Genome Project, told me in an interview. “It makes them feel like they're making great progress. I think science should be focused on accumulating knowledge. Now, sometimes you have to accumulate a certain amount of data to accumulate new knowledge, but way too much of science is an endpoint of accumulating data.”

In fact, since massive genome sequencing projects have emerged, data have generated confusion. Cancer researchers expected to find similar cancer-causing mutations, but found that healthy tissue can contain more mutations than many tumors, and the mutation frequencies of patients with the same cancer type can vary by three orders of magnitude. Even in disorders which are attributed to a single responsible gene, individuals with and without a disease can have the same genetic mutations, and mutations can damage gene function but not cause disease manifestation. Clearly, given such genetic heterogeneity, we will have to carefully consider how we structure research fields like precision medicine.

Throughout this column, I’ve examined many aspects of the scientific process, from funding mechanisms and reproducibility to peer review and public communication. In each step, uncertainty underscores how the science operates and its social implications.

To increase understanding of science, then, it is necessary to acknowledge and contextualize uncertainty, not hype up or ignore it, both to the public and among scientists. We must embrace uncertainty as we continue along this endless frontier.

Julie Heng ’24 is a Crimson Editorial editor. Her column runs on alternate Tuesdays.

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