“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.
- Automated science is “moving the role of the scientist higher and higher up the food chain,” says Murphy. Researchers are focusing their efforts on big-picture problem-solving rather than on the nitty-gritty of running experiments.
- He says it will also allow scientists to take on more problems at once — and solve big, lingering ones that are too complex to tackle right now.
Connect that to the increased costs of scientific research, as I explored in The Hidden Economics of Ideas
earlier this year, and you’ll conclude that expanded use of AI in scientific research is the only way to go.