Is science neutral? Often, when we think of someone who works in science, one person comes to mind rational, rigorous, immune to prejudices and external pressures. Someone who manages to rise above personal opinions to observe reality in the most objective way possible and thus make science neutral and impartial. In practice, this is not entirely true: science is done by people and peopleeven the most rational, Not they are neutral.
Be careful, though: this doesn’t mean that science is just an opinion or that scientific results are as good as any other idea. It means that the production of scientific knowledge it is a human activity and, like all human activities, it inevitably reflects the historical contextcultural, economic and social in which it was born.
This lack of neutrality leads to very real consequences in the real world. One of the areas in which it is most evident are the medical sciences: for decades, women, the elderly and minorities have been underrepresented in clinical trials, with the result that numerous therapies have been developed and validated mainly on the Western male population, making them less effective for other populations.
Understanding that science is not neutral does not mean questioning its reliability. On the contrary, it means understanding how scientific knowledge is produced, recognizing its limitations and continuing to improve it. It’s right there awareness of these limits which allows research to correct its errors and become, over time, increasingly reliable.
Let’s see what the problems of scientific research are, what impacts it has had on medical research and why, despite everything, we can trust science.
Practice and the scientific method are not the same thing
To understand why science is not neutral we must distinguish the scientific method from the research practice.
The scientific method is probably the best method that humanity has developed so far for producing reliable knowledge. It is based on the observation of a phenomenon, on data collectionon the formulation of a hypothesis, on verify of the same through experiment, on the formulation of a law and on the possibility of replicating the results.
This method is designed to minimize theinfluence of opinions and the prejudices of those who do research. The problem, however, is that in practice science is done by people. It is people who decide which phenomenon is worth observing, what questions to ask, which data to collect and with which tools. All these decisions inevitably depend on the historical and cultural context, on the resources available, on the priorities of those funding the research, on the questions considered most urgent and even on the internal incentives of the academic system. One of these is the so-called “publish or perish”, the mechanism that links the career of those who do research to the number of articles published and which, consequently, encourages the production of scientific articles containing results that are of little relevance or even cannot be replicated.
As the American political scientist wrote Daniel Sarewitzwhose work focuses on the relationship between scientific research and society:
Science has always been political, and scientists are not monastic explorers of truth.
One of the scientific fields in which the effects of human and cultural biases are more evident and have more serious consequences is that of medical and clinical research.
Clinical research is not neutral
For decades, clinical research has conducted its own tests on subjects masculine And Westernersstarting from the implicit assumption that the results were then applicable to other populations. This, however, has made it much more difficult to recognize and treat some pathologies.
In the case of cardiovascular diseasesFor example, two studies from the University of British Columbia and the Cardiology Department of Sydney Hospital, published in 2022 and 2024, reported a underrepresentation of women in clinical trials. This deficiency has led to greater difficulty in recognizing some cardiovascular pathologies that are more frequent in women, increasing the risk of late diagnoses and inadequate treatments.
Another example of research bias involves industry-sponsored drug studies. A 2018 study conducted by a Danish hospital highlighted that the studies financed by companies they report results and conclusions more often favorable al product sponsored. This does not mean that every industry-funded study is necessarily unreliable, but that the funding system can also influence the production of knowledge, the way in which results are communicated and can lead to greater use of a certain type of drug.
The science is reliable
At this point it is important to avoid a misunderstanding. Saying that science is not neutral and that it can make errors does not mean arguing that all opinions have the same value or that the knowledge produced by scientific research cannot be trusted. The strength of science lies precisely in the fact that it was built for limit the effect of bias individuals on collective knowledge. There revision among equals, the replicability of the experiments and the sharing of data are processes designed exactly with this objective.
There is also another, more practical reason why it is worth trusting science: works. Vaccines have dramatically reduced infant mortality; electricity, studied with experiments that seemed absurd at the time, is the basis of most of our daily activities; weather forecasts, while remaining imperfect, continually improve thanks to the accumulation of new data and the continuous revision of models.
Science does not produce absolute truthsimmutable and free of bias, but knowledge that can be corrected, expanded and refined over time. And it is precisely here that the awareness of its limits becomes a strength. Recognizing bias, designing more representative studies, and building a more diverse scientific community not only makes research more equitable, but also more robust. More perspectives mean better questions, more robust data, and an increasingly accurate understanding of the world.
