"We're in the middle of a paradigm shift, a time when the choice of experiments and the execution of experiments are not really things that people do," says Bob Murphy, the head of the computational biology department at Carnegie Mellon University. Details: Experimental science is expensive. In biology, for example, pricey equipment and labor mean that scientists can't do all the experiments they would like. Instead, they have to prioritize the ones they think will give them the most information about the questions they are after, and then extrapolate to estimate the outcomes of the experiments they didn't do. Automating science makes it easier to do big experiments, allowing more people to participate -- and potentially boosting the scientific output of countries that have traditionally trailed the U.S.