Joint HPS seminar with the Department of Science Education: Niels Linnemann
Niels Linnemann and Robert Michels, “Can AI help Humeans? The laws of nature debate in light of automated scientific discovery”
According to the standard Humean theory of the laws of nature, Lewis's Best System Analysis, laws of nature have this status at least partly as the result of an optimal trade-off between scientific values such as simplicity and descriptive strength. This idea has recently come under pressure, since --- as authors like Roberts and Woodward have pointed out --- there might, pace what
Humeans like to suggest, be no such trade-off in the way laws of nature are identified in the natural sciences. Recent developments in the field of automated scientific discovery, in particular regarding symbolic regression, promise to provide Humeans with an answer to this challenge and, as we will argue, might even allow them to, in turn, put pressure on rival theories of the laws of nature: Symbolic regression gives us a method for (re)discovering laws which closely matches the Humean picture of what makes a law of nature a law of nature and in particular crucially involves a trade-off between simplicity and descriptive strength. In this paper, we discuss whether Humeans can indeed rely on symbolic regression to bolster their theory of laws of nature.
This talk is jointly organized by the Research Group on History and Philosophy of Science at the Department of Science Education and the Niels Bohr Archive.