In many areas, decision-making is affected by the difficulty in producing reliable forecasts. The behavior of financial markets, consumers or weather phenomena, the evolution of an ecosystem or the movement of certain celestial bodies provide some examples of unpredictable events that have an impact on human activity. Some developments of mathematics can help reduce this unpredictability or, at the very least, analyze it from a strategic point of view. The theory of probability plays such a role but so do fluid mechanics in the study of turbulence, or dynamic systems in the study of so-called chaotic phenomena, which belong to a specific class of unpredictable phenomena.
Students, as well as the public, often raise questions about the scientific nature of economics. Indeed, while economics uses very sophisticated mathematical models, their predictive success leaves much to be desired. Yet, economists feel that they learn a lot from these models. It is argued that part of economic theorizing does not follow the Popperian view of science; rather, some of the knowledge that is generated is analogical. According to this view, research in economics attempts to serve rhetorical purposes. As such, analogies can be useful, alongside general rules. Moreover, the role of axiomatic decision theory is understood as serving to clarify arguments in the context of public debates.
Advances in medical imaging make this discipline a laboratory for the latest scientific methods. Disruptive innovations stemming from the convergence of medicine and physical sciences lead to fundamental questions: is there a place for experts against machines? How to reconcile statistical data, mass produced by new devices, with a focus on he who is central to medical practice: the individual?
Looking for balance between science and technology in modern research, we can observe it is the latter in the ascendant. Research is being dictated by the availability of technological resources but in the past, the reverse was true. Projects began by a review of the available data from which a scientific hypothesis was constructed, and finally a search for the best technological tools would begin. Francoise Barre-Sinoussi, who was awarded the Nobel prize in 2008, suggests that in the rush to embrace technology, researchers may be missing the chance to learn from what worked so well in the past.
How are we to assess the distance between basic research and the essential technologies of the modern age? Are we in the process of building the bridge that will unite the two domains or is the gulf between them growing wider by the day? Reconciling the interested parties in any definitive way remains difficult as each side can furnish multiple examples to support their perspective on the matter.