How can we gain knowledge of the natural world without conducting real and direct experiments? That is, how can we investigate a target system (for instance a black hole) without ever observing or manipulating it? It is this question that I tackled during this project. For that, I analysed different scientific tools such as Analogy and Analogue Experiments, Models, Thought Experiments and Computer Simulations. These tools permit "surrogative reasoning"; scientists investigate material and/or theoretical accessible systems in order to draw conclusions about -- usually inaccessible -- target system. Surrogative reasoning is thus an effective form of scientific thinking especially used when scientists do not have direct empirical access to the target systems. It is increasingly adopted in various scientific fields, as it is the most (sometimes only) effective way to draw inferences when direct experimentation is precluded: for instance, because the target system is too far away (e.g. black holes), too small (e.g. elementary particles), too complex (e.g. climate), too expensive to construct (e.g. real-scaled bridges), unethical/dangerous to experiment on (e.g. pharmacology). Notwithstanding its ubiquitous role in science, the epistemological foundations of surrogative reasoning raise outstanding philosophical issues. E.g. the conclusions of its inferences are neither logically certain, nor empirically grounded – which opens a series of questions with respect to the confirmation and disconfirmation of hypotheses through surrogative means. My projects tackled such issues from an integrated history and philosophy of science perspective.
Why is it important for society?
Society faces at least two major challenges: Climate change and the Coronavirus Pandemic. To tackle both, decision makers are relying more and more on science. In investigating these topics, scientists mainly rely on results generated by the above tools that permit surrogative reasoning, seeing that direct experiments on real populations and on the climate are precluded. For instance, they construct and investigate hypothetical and counterfactual scenarios in order to draw conclusion about the evolution of the climate and the pandemic. This is one aspect of the project that is the most relevant to society. I took the notion of scenario seriously and started analysing its role in science. Indeed, it is important to understand the kind of knowledge and predictions/projections reasoning on scenarios could provide. Understanding this helps clarifying some mischaracterization concerning the use of science in policy, thus reducing scepticism against science, something we desperately need. My research on scenarios is ongoing with a new project on climate science.
What are the overall objectives?
The project tackled two main objectives: First, I articulated and defended a novel epistemic account of scientific thought experiments that characterizes their function as inconsistency revealers and resolvers. In it, the notion of scenario played a central role.
Second, I started a larger project on surrogative reasoning in which I aim at doing a comparative analysis between several tools and their epistemologies, in particular between Thought Experiments, Computer Simulations, Scientific Models, and Analogical Experiments.
