British scientists say they may have invented themselves out of a job.
A new robotic system they developed can, for the first time, independently design and carry out a genetics experiment, and then interpret the results.
No difference was found between the lab bench results generated by the robot scientist and those gathered by graduate students doing similar work, the researchers report in Thursday’s issue of the journal Nature.
While the system remains in its infancy, they hope it will someday conduct lab-intensive work, freeing human researchers from drudgery.
“The sort of grunt research can be done this way, and more creative stuff humans will have more time to do,” said study author Stephen Oliver of the University of Manchester.
Other researchers described the robot as a “harbinger of the future,” but said more sophisticated reasoning software had to be developed.
Once that happens, labs would adopt such advanced artificial intelligence systems “pretty rapidly and pervasively,” said Larry Hunter, a computational biology expert at the University of Colorado School of Medicine, who was not involved in the experiment.
In the automated experiments, the researchers first developed a mathematical model showing how various genes, proteins and enzymes and growth mediums interact.
Armed with that knowledge, the robot independently generated hypotheses about the missing genes, then used equipment to grow yeast strains. Later, the growth of each strain was measured to evaluate the original hypothesis. The process was repeated over and over as the system developed new hypotheses based on the accumulating data.
“It’s like if you have a machine which is broken, the system can automatically reason to find all the possible ways it can be broken,” said Ross King of the University of Wales-Aberystwyth. “Some philosophers have thought this is impossible for computers, because that’s the imaginative leap.”
“If this person committed the crime, all the clues make sense,” King said.
Hunter said the new work marks the first time that experimental design, computer control of instruments and analysis of the resulting data have been “hooked together in a closed loop.”
“It is now possible to design artificial intelligence systems that are able to reason well enough to be effective partners in scientific research,” Hunter said.
Oliver said the next step is to see whether the robot can make a completely novel discovery rather than simply match the graduate students’ results.