Science is learning more and more, but we risk understanding less and less

A piece of information can be public yet remain inaccessible. It is enough for it to be buried beneath other information, whilst a simpler, more eye-catching news item attracts attention. It is a form of concealment suited to an age in which content production is growing relentlessly: the data is available, but it becomes difficult to understand its significance and how it fits in with what we already know.

Science provides a particularly clear example. In 2025, according to the estimate cited by Helen Pearson in Aeon, around seven million scientific articles were published – over 19,000 a day. Each study may contribute a useful finding; when presented in isolation, however, it can create a misleading impression. Newspapers report on the latest research; readers are confronted with headlines that appear to contradict one another, and the bigger picture remains out of focus.

This happened with paracetamol during pregnancy. In September 2025, the US regulatory agency, the FDA, issued a warning based on a possible link between taking the medicine and autism in children. The news caused a great stir. A subsequent review of the body of evidence concluded that the available data did not clearly show a link to autism or ADHD. In the meantime, the alarm had reached many women, while the comprehensive assessment required the less high-profile work of reviewing the literature and evaluating the quality of the studies.

In cases such as this, the necessary knowledge is not limited to a single publication. It takes shape by comparing results, distinguishing the most robust studies and assessing what they indicate as a whole. A systematic review brings together relevant studies according to stated criteria and assesses their reliability; where the data are comparable, a meta-analysis combines the results. These methods were developed precisely to make sense of a body of literature which, when viewed as the sum of individual articles, may appear contradictory.

The history of the recommended sleeping position for newborns illustrates the cost of delayed action. For decades, it was recommended that babies be placed on their tums. A subsequent review revealed that the risks associated with that position were already apparent in studies conducted around 1970 – some twenty years before the advice changed widely. Researchers estimated that a timely synthesis of the evidence, followed by appropriate action, could have prevented at least fifty thousand deaths in Europe, Australasia and the United States. The estimate is counterfactual, and for this very reason should be interpreted with caution; nevertheless, the case demonstrates that the accumulation of findings is not sufficient to produce the kind of knowledge capable of guiding decisions.

Science has developed tools to carry out this work. Gene Glass’s meta-analysis in the 1970s helped move beyond the rudimentary counting of favourable and unfavourable studies, which assigned equal weight to research of varying sizes and with differing effects. The establishment of the Cochrane Collaboration in 1993 brought the concept of systematic review to the forefront of medicine. Yet the scientific system continues to prioritise the publication of new findings above all else. Synthesis takes years, does not always produce a catchy headline and struggles to compete for attention with the latest study.

Digital growth also turns this challenge into a question of power. To access scientific literature, we rely on search engines, platforms and artificial intelligence systems that rank pages and decide which results to show us. Their selection process is inevitable; the way in which it is carried out often remains opaque. The few large companies that control these tools thus become gatekeepers of scientific information: they determine which content comes to the fore, which is summarised and which remains buried on subsequent pages. This selection process influences what the public can learn and what evidence informs decision-making.

A response generated by artificial intelligence makes the filtering process even less transparent. The user receives a pre-organised conclusion, without always knowing which studies were consulted, which were excluded, or how reliable the sources considered are. Some tools can help identify and classify articles, speeding up parts of the work; however, their ability to produce reliable reviews must be demonstrated, and an automated summary may provide an incomplete picture of the literature. Efficiency in locating publications is not the same as the ability to evaluate them.

The public issue, then, concerns who controls attention and according to what criteria. If the filtering is entrusted to proprietary systems, whose criteria cannot be verified, the formal availability of articles coexists with access governed by private decisions. We need transparent search tools and up-to-date scientific summaries that are accessible and verifiable; it is also essential to make the sources and the process leading to a conclusion transparent. Scientific knowledge is built when results are organised and subjected to scrutiny. In an environment saturated with information, those who decide what deserves attention wield decisive power over what society is able to know.