Lab Robot Discovers Scientific Knowledge on its Own
Researchers have created a robot scientist which they believe is the first machine to have independently discovered new scientific knowledge. The laboratory robot, called Adam, is a computer system that fully automates the scientific process. Adam is designed to carry out each stage of the scientific process automatically without the need for further human intervention.
The robot has discovered simple but new scientific knowledge about the genomics of the baker’s yeast Saccharomyces cerevisiae, an organism that scientists use to
model more complex life systems. The researchers, based at Aberystwyth University and the University of Cambridge, have used separate manual experiments to confirm that Adam’s hypotheses were both novel and correct.
Using artificial intelligence, Adam hypothesized that certain genes in baker’s yeast code for specific enzymes which catalyze biochemical reactions in yeast. The robot then devised experiments to test these predictions, ran the experiments using laboratory robotics, interpreted the results and repeated the cycle.
Adam is a still a prototype, but Professor Ross King, who led the research at Aberystwyth University, believes that their next robot, Eve, holds great promise for scientists searching for new drugs to combat diseases such as malaria and schistosomiasis, an infection caused by a type of parasitic worm in the tropics.
“Ultimately we hope to have teams of human and robot scientists working together in laboratories,” King said. “If science was more efficient, it would be better placed to help solve society’s problems. One way to make science more efficient is through automation. Automation was the driving force behind much of the 19th and 20th century progress, and this is likely to continue.”
Professor Douglas Kell, Chief Executive at the Biotechnology and Biological Sciences Research Council (BBSRC) that funded the research, said: “Computers play a fundamental role in the scientific process, which is becoming increasingly automated, for instance in drug design and DNA sequencing. This has led to more scientific data, increasingly available on the Web, which in turn requires an increased use of computers to analyze these data. Robot scientists could provide a useful tool for managing such data and knowledge, making scientific procedures easier and more efficient. This kind of learning will become even more important as we move further towards integrative and predictive biology in the era of Web 2.0 and the Semanti Web.”
The work has been published in the journal Science.
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