Automating Science using Robot Scientists

Ross King
University of Science and Technology in Manchester (UMIST)

A Robot Scientist is a physically implemented robotic system that applies techniques from artificial intelligence to execute cycles of automated scientific experimentation. A Robot Scientist can automatically execute cycles of hypothesis formation, selection of efficient experiments to discriminate between hypotheses, execution of experiments using laboratory automation equipment, and analysis of results. The motivation for developing Robot Scientists is to both to better understand the scientific method, and to make scientific research more efficient. The Robot Scientist ‘Adam’ was the first machine to autonomously discover scientific knowledge: both formed and experimentally confirmed novel hypotheses. Adam worked in the domain of yeast functional genomics. The Robot Scientist ‘Eve’ was originally developed to automate early-stage drug development: integrating drug screening, and active machine learning for Quantitative Structure Activity Relationship (QSAR) learning. More recently my colleagues and I have adapted Eve to work on yeast systems biology, and cancer. We argue that it is likely that advances in AI and lab automation will drive the development of ever-smarter Robot Scientists. The Physics Nobel Frank Wilczek is on record as saying that in 100 years’ time the best physicist will be a machine. If this comes to pass it will transform our understanding of science and the Universe.

Presentation (PDF File)

Back to Workshop I: From Passive to Active: Generative and Reinforcement Learning with Physics