Make way for robot scientists

Emma Louise Byrne, Maria Liakata, Kenneth Edward Whelan, Stephen G. Oliver, Jeremy John Rowland, Wayne Aubrey, Larisa Nikolaevna Soldatova, Andrew Charles Sparkes, Michael Young, Magdalena Markham, Amanda Janet Clare, Pinar Pir, Ross Donald King

Research output: Contribution to journalLetterpeer-review

9 Citations (Scopus)


In their 19 June letter ('Machines fall short of revolutionary science,' p. 1515), P. W. Anderson and E. Abrahams, commenting on our work on the automation of science, state that we are 'seriously mistaken about the nature of the scientific enterprise.' Their argument seems to be based on two premises: (i) There are two types of science, normal and revolutionary, and normal science 'does not contribute very much to the advancement of knowledge.' This view dismisses as unimportant the vast bulk of science, and must surely be wrong. (ii) Whereas normal science may be automated, revolutionary science never will be, as there is no possible 'mechanism.' It is certainly true that revolutionary science cannot currently be automated, and in our Report ('The automation of science,' 3 April, p. 85) we described the automatically generated science as 'modest...but not trivial.' Nevertheless, the inability of some critics to imagine a mechanism does not eliminate the possibility that one exists. Indeed, the mechanism we propose is the one that has been successfully applied to chess: There is a continuum in player skill, and computers slowly improved with advances in computer hardware and software until they now play at world championship level. We argue that there is a similar continuum in the ability to do science, from what robot scientists can do today, through what most human scientists can achieve, up to the level of a Darwin or Newton. The Physics Nobel Laureate Frank Wilczek has said that the best chess player in the world is 'non-human' and that this may well be true for the best physicist in 100 years time (1). Finally, Anderson and Abrahams ignore the possibility of machines and humans working together to do revolutionary science that neither could do alone.
Original languageEnglish
Pages (from-to)945
Number of pages1
Issue number5943
Publication statusPublished - 21 Aug 2009


  • Artificial Intelligence
  • Automation
  • Robotics
  • Science


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