What does AI mean for chemistry?
Phil Ball looks at whether letting machines do our thinking for us will change our understanding of chemistry itself
Today’s AI, based largely on machine-learning algorithms that can mine huge data sets for patterns and correlations, seem best regarded as an assistant to, rather than a replacement for, the human researcher. It can do an awful lot, especially when coupled to robotic systems: not just analyse data but plan and execute experiments, make iterative improvements and even formulate and test specific hypotheses. Little of this is yet routine in the laboratory, but it is becoming ever more so.
In some ways, chemistry is ripe for AI colonisation. A great deal of chemical synthesis makes use of tried-and-tested methods and synthetic pathways that even those conducting them find dull and repetitive. But it’s too simplistic to frame these developments in terms of the ‘demise of the human chemist’. At least in the near term, it’s more likely that the roles and the skill sets of chemists will shift. Eliminating the burden of repetitive tasks is hardly to be lamented, since it might free up chemists to think creatively rather than to slog routinely.
It might be more edifying to ask whether AI might change chemistry conceptually.