Numerical methods, understood in the broad sense including computer simulations, digital microscopic imagery, high performance computers, not to mention diverse AI based tools in their diversity, are becoming an integral part of the contemporary scientific practice. This is not inherent to experimental disciplines, relying on observations and modeling. For example automatic proof assistants are a large domain of research at the frontier of mathematics and theoretical computer science. Furthermore social sciences such as linguistics and sociology for example, developed respectively sub-branches of computational linguistics and computational sociology. Another case concerning the use of numerical methods concerns the social and political impacts of the change in the relationship to information. The centralization and digitalization of health care documents change the hierarchy relative to information communication between workers of hospitals, not to mention diverse AI based tools that become central in decision making. Whether they are inherent methodological research tools or used outside of the scientific protocol, they all rely on a specific interpretation of the information in order to render the manipulation of the data automatic. Those tools thus imply a symbolic approach to the data, formalized and abstracted from its original content, in order to make it subject to a computational procedure as it was made possible by the development of computer science. This event aims at questioning the methodological as well as the ontological implications of the numerization of the data in the scientific practice. Working with numerical data, interpreting quantitative results into a qualitative theory, developing new measuring instruments allowing the manipulation of broader sets of data, are as many ways of approaching the questions of how our practices shape the need to make pre-theoretical assumptions towards the object of knowledge. This raises different problems. For example is there a distance between the manipulated data and the object of study, or is this distance forgotten and reduced to its representation through the process of numerization or measurement? How well is this stance towards the object of a particular scientific domain represented or explicit in the different scientific communities?
In order to sketch the different approaches to these questions, the goal of this event is to bridge together natural and social sciences with formal domains like computer science, mathematics and logic. The main expectation for this conference is on one hand for computer scientists, mathematicians and logicians to engage in a reflexive look on what their technical results are used for and what properties of the formal objects they study lead to these uses. And on the other hand, sociologists, historians, historians of art, biologists, researchers in cognitive sciences, environmental studies, as well as in law and political studies will be asked to have a critical approach to the digital objects they use in their practice and what choices these digital tools lead them to make towards their object of study.