Artificial intelligence has a feel for laboratory science
Researchers at Southampton University’s School of Electronics and Computer Science (ECS) have won an award for producing an artificial intelligence that is able to guide scientific experimentation within a laboratory.
PhD students Chris Lovell and Gareth Jones received the Carl Smith Award on 8 October for best student paper at the 13th international conference on Discovery Science.
The artificial intelligence, developed by Chris Lovell, is claimed to mimic the techniques used by human scientists.
The ‘artificial experimenter’ software looks at the data available, builds hypotheses and then chooses the experiments to perform, all without human interaction.
‘Experimentation is expensive. Scientists always want to learn as much as they can from the smallest number of experiments possible. The new techniques we have developed try to address this problem,’ said Dr Klaus-Peter Zauner of the Science and Engineering of Natural Systems Group at ECS, who supervised this research as part of a Microsoft European Fellowship.
As well as learning from small numbers of experiments, the software is designed to question whether the data obtained is correct.
‘Biological experimentation can be error prone,’ Dr Zauner added. ‘Measurements taken may not always be representative of what actually happens. Our system tries to detect erroneous data, so it can ignore it.’
The artificial experimenter has been used to characterise the response from a biological system. Currently these experiments have been performed manually in the laboratory, but the next step is to join the software with an automated platform that can perform microscale experiments, to allow for fully autonomous experimentation.
The lab-on-chip platform, being developed by Gareth Jones, will allow the cost of experimentation to be reduced further, by decreasing the volumes of chemicals required per experiment.
When completed, the platform will perform the experiments requested by the artificial experimenter, providing it with the results obtained to allow the software to develop new hypotheses and decide on the next experiments to perform.
The work has been carried out as part of a Microsoft European Fellowship awarded to Dr Zauner, along with collaboration from Prof Steve Gunn and Prof Hywel Morgan.
‘The artificial experimenter will provide a tool for scientists, which will not only allow them to reduce experimentation costs, but will also allow them to redirect their time from monotonous characterisation experiments, to analysing the results, building theories and determining uses for those results,’ say the researchers in their paper.