Can scientific discovery be automated?
The Atlantic - 04/25/2017
Other, more recent approaches, such as those of Andrey Rzhetsky at the University of Chicago and Albert-László Barabási at Northeastern University, rely on mathematical modeling and graph theory. They incorporate large datasets, in which knowledge is projected as a network, where nodes are concepts and links are relationships between them. Novel hypotheses would show up as undiscovered links between nodes.
The most challenging step in the automation process is how to collect reliable scientific observations on a large scale. There is currently no central data bank that holds humanity’s total scientific knowledge on an observational level.