Title: Automating the Scientific Method Abstract: In the last decade we have seen computer science, statistics, and the earth, space, life and social sciences come together with a new synergy based on the common goal of data analysis. These multi-disciplinary interactions have become necessary as we pursue both high quality data analysis as well as analysis of extremely large data sets. However, the ultimate goal is more fundamental than mere data analysis. We aim to automate the scientific method itself. The scientific method relies on the cyclic application of three activities: hypothesis generation, inquiry (experimental design) and inference (data analysis). The majority of our efforts at this point have been focused on the process of automating inference. However, little attention has been paid to automating the processes of inquiry and hypothesis generation. The most scientifically-useful approach to data analysis is model-based. I will briefly review the methodology behind automating model-based inference with a focus on Bayesian probability theory. I will then introduce a new related methodology called the inquiry calculus, which enables the automation of model-based inquiry. Automated hypothesis (model) generation will be left for another day, as it is the least advanced of the three technologies. I will demonstrate the application of automated inference and inquiry with a robotic scientist that performs its own experiments and analyzes its own data.