This is my Marie Sklodowska Curie Award project (grant no. 101106919), which began in November 2023. The purpose of the project is to identify a new ontology for causal modelling in the sciences in terms of powers. The research will bring together the causal modelling practices of the applied sciences (e.g. computational engineering) with ongoing research in the metaphysics of powers. Updates will be posted below as the project develops.
Project Summary
Multiple causal modelling techniques are employed in the applied sciences. For instance, Structural Equations Models (SEMs) are employed in genetics, econometrics and psychology; Fault Tree Analyses (FTAs) are employed in aerospace and nuclear engineering; Petri Nets are used in traffic control and integrated computational systems. Each technique has a unique way of representing causal phenomena, drawing on different data and background information. But what is it about the world that allows each of these techniques to work? And what makes each technique a representation of causal phenomena specifically? POCAM will break new ground answering these questions by determining a single, underlying causal ontology within the powers metaphysics framework. In doing so, POCAM will provide an explanation of why such varied causal modelling practices are so successful, thereby helping practitioners better conceptualise the connections among different modelling formalisms and with our pre-scientific understanding of causation in everyday life.
While there have been attempts to determine an underlying ontology for SEMs there has yet to be any philosophical engagement with FTAs or Petri Nets, despite their pervasiveness in science. Moreover, current ontologies for causal models in metaphysics fail to be adequately reductive, preventing them from being truly explanatory. POCAM will therefore be pioneering in its attempt to provide a single reductive ontology of all three modelling techniques. To do so, POCAM will draw on the scientific credentials of the powers metaphysics framework. The nature of powers and their role in causation is increasingly well understood but has yet to be brought into sustained theoretical engagement with the casual modelling literature.