To what extent can scientific discovery be automated? Where are the areas where automation can make the biggest contribution to human efforts? These questions and a number of others are addressed in a very interesting 2-part review article on “Automated Discovery in the Chemical Sciences”. As the authors say, “The prospect of a robotic scientist has long been an object of curiosity, optimism, skepticism, and job-loss fear, depending on who is asked” I know that when I’ve written about such topics here, the comments and emails I receive cover all those viewpoints and more. Most of us are fine with having automated help for the “grunt work” of research – the autosamplers, image-processing and data-analysis software, the plate handlers and assay readers, etc. But the 2 things that really seem to set off uneasiness are (1) the idea that the output such machinery might be usefully fed into software that can then reach its own conclusions about the experimental outcomes, and (2) the enablement of discovery through “rapid random” mechanized experimental setups, which (to judge from the comments I’ve gotten) is regarded by a number of people as a lazy or even dishonorable way to do science.

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