From Uncertainty to Understanding: The Scientific Process

We often see headlines giving the impression that scientists have changed their mind. One day, “Coffee increases the risk of heart disease!”, and the next, “Coffee helps you live longer!”. Eggs were once villainised for raising cholesterol, then celebrated as an essential protein source. Sleep recommendations shift from “No more than 8 hours per night” to “At least 9 hours for optimal health”. Pluto lost its planetary status. Einstein was proven wrong. Dinosaurs were cold-blooded, then warm-blooded, then something in between. How can scientists be so confused? Can we really trust science?

In reality, science is not about sudden flip-flops - it is an evolving process of refining our understanding based on new evidence. When a single study is picked up by the media without context, it can create the illusion that scientific opinion swings wildly. But each new finding is just one step in a much longer journey of gathering, testing, and refining knowledge.

Sensational headlines thrive on making science seem like a rigid, all-knowing system that delivers instant, universal truths. But science doesn’t deal in absolute certainty - it builds knowledge gradually, adapting as new evidence emerges. This uncertainty is not a weakness; it is a strength. The ability to question, test, and refine ideas is exactly what makes science the most reliable way to understand the world.

To better understand the reliability of science in the media, we need to look at how the scientific method actually works.

Note: This is a vast and complex topic that has been explored for centuries in the philosophy of science. Here, we offer a concise overview of key ideas to consider when interpreting new scientific discoveries. For those interested in a deeper dive, we recommend this resource.

Scientific progress is not a smooth, linear journey. There are periods of rapid breakthroughs and times when progress seems to stall. Changing established knowledge requires a significant amount of research and collaboration. Unlike the dramatic portrayals in movies, science is rarely about a lone genius making a sudden, groundbreaking discovery. Instead, progress is typically built on the collective efforts of many researchers over time.

Even Albert Einstein, often seen as the epitome of a lone genius, did not work in isolation. His theory of General Relativity was developed alongside contributions from other physicists and mathematicians. It took years of rigorous testing and refinement before it was fully accepted by the scientific community.

Progress often begins when an anomaly is observed - something that does not quite fit with existing theories or expectations. In response, scientists develop a hypothesis, a testable idea that seeks to explain the phenomenon. This might stem from direct observation or from a theoretical question that challenges established understanding.

For example, in the late 19th century, Marie Curie observed that certain minerals, particularly uranium ores, emitted energy even when they were not exposed to sunlight. This anomaly could not be explained by existing physics at the time. Curie hypothesized that this radiation was coming from the atomic structure of the elements themselves, leading to her discovery of radioactivity. Her work not only expanded scientific understanding but also paved the way for developments in nuclear physics and medical treatments like radiation therapy.

New questions do not necessarily mean that previous knowledge was wrong. Often, they help improve or expand upon it.

In the 1970s, some scientists noted a temporary cooling trend and explored whether it might indicate a longer-term shift toward an ice age. However, the broader scientific community was already gathering evidence on greenhouse gas emissions and their warming effect. As data accumulated, it became clear that short-term cooling was a local fluctuation, whereas the dominant long-term trend pointed toward global warming. This wasn’t a case of science being wrong and then reversing—it was an instance of refining conclusions as more evidence became available.

To test a hypothesis, scientists use models - simplified versions of complex reality - that allow them to study a phenomenon in a controlled way. A model might be a computer simulation, a mathematical equation, or a small-scale physical experiment that mimics real-world conditions. Models allow scientists to test ideas, explore possible outcomes, and determine whether the evidence supports or challenges a hypothesis. Models can be updated and refined as new data becomes available.

When studying a new drug, researchers first test its effects on a simpler model, such as individual cells in a lab. This helps isolate the drug’s effect under controlled conditions, ensuring that any changes are due to the drug itself. However, this does not tell us everything about how the drug will behave in a more complex system, like the human body.

The results of this initial study help determine whether the evidence supports or contradicts the hypothesis. If the hypothesis is contradicted, scientists refine their ideas and develop a new, more informed hypothesis. In this way, science is always progressing - negative findings are just as valuable as positive ones, helping to eliminate incorrect assumptions and refine our understanding.

However, in science, testing a hypothesis rarely leads to an absolutely certain conclusion. Instead, researchers rely on probability to determine how likely it is that their results are due to the hypothesis rather than random chance. The stronger and more consistent the evidence, the greater confidence scientists have in their conclusions. In this way, new data or improved methods may refine or even challenge previous findings. This is why scientific knowledge is always evolving.

Weather forecasting has a common and widely familiar reliance on probability. Meteorologists use statistical models to analyse variables such as temperature, air pressure, and humidity to predict future conditions. However, because weather systems are highly complex, forecasts always exhibit a degree of uncertainty. And as we all know, these uncertainties can lead to unexpected changes!

Early results from a single study are just the first step in scientific progress. They rarely lead to immediate consensus. The next phase involves expanding the research, testing it under different conditions, and gradually building a more complete understanding. Reproducibility is crucial - other scientists must be able to repeat the study and obtain similar results before findings are widely accepted.

Once enough research has been conducted, and findings are supported by extensive data and statistical analysis, a hypothesis can become part of an established scientific framework.

Is this the end? Even at this point, new discoveries, technologies, and methods can refine or even replace existing frameworks, leading to an ever-improving understanding of nature. This is what makes the scientific method exciting - it is always evolving.

For example, Newton’s law of universal gravitation accurately described planetary motion within our solar system. However, as scientists studied gravity on larger cosmic scales, Newton’s equations no longer held up. This led to Einstein’s theory of General Relativity, which provided a more complete explanation. But even General Relativity isn’t the final answer - new theories continue to emerge as we deepen our understanding of the universe.