Artificial Intelligence is revolutionising the way science is produced, analysed, and disseminated. It’s not the future, but a present reality.

Artificial intelligence (AI) is revolutionising the way science is produced, analysed, and disseminated. This is not a distant prospect but a present reality: the tools already exist and are increasingly integrated into the daily work of researchers. The real question, therefore, is what role humans will play in a context where AI is fully operational.

Every research project starts from existing knowledge, traditionally acquired through a long and complex literature review. AI, however, can scan millions of articles in just a few moments, extract the most relevant information, and build an updated overview of current knowledge, with a research capacity and memory that no human being could ever achieve.

Yet AI does not stop at summarising what we already know: it can identify knowledge gaps and suggest the most relevant research objectives, highlighting which studies might have the greatest scientific, social, or environmental impact.

The next step is the experimental design, an area where AI is already widely applied. It can calculate sample sizes, optimise randomisation, anticipate confounding variables, and propose appropriate statistical approaches. It will then be up to the researcher to concretely implement the plan developed by AI, carrying out experiments in the field or in the laboratory.

Data collection brings further support: AI will analyse the data, detect patterns and correlations, and draw conclusions. Moreover, it can draft article manuscripts, enrich them with updated bibliographies, and even recommend the most suitable journal for publication, considering impact factor, review times, costs, and thematic relevance. In scientific dissemination too, AI will provide powerful tools: abstracts, posters, presentations, as well as outreach and multimedia materials, all produced quickly and effectively.

This raises a crucial question: what will remain for the researcher? If AI can search, select, design, analyse, write, and disseminate, what space is left for humans? The answer lies in the very essence of science: asking new questions, giving meaning and direction to data. AI may guide and support, but it will always be the researcher’s task to give value to what AI produces.

The future of science, therefore, will not belong exclusively either to machines or to humans, but will emerge from collaboration. The challenge is not to choose between artificial and human intelligence, but to learn how to make them work together.

Source: Newsletter EAAP n. 282