The Strategic Priorities Fund of United Kingdom Research and Innovation has awarded £9.2 million to the Alan Turing Institute, the British Library and researchers from different universities to fund the five-year ‘Living with Machines’ project.
The aim of the project is to develop new methods in data science and artificial intelligence that can be applied to historical resources, producing tools and software to analyse digitised collections at scale. Living with Machines will bring together data scientists, curators, historians, geographers and computational linguists.
Adrian Smith, director of The Alan Turing Institute, said: “We can analyse vast amounts of data at a huge scale and uncover new insights and questions, as in this timely project with the British Library which will apply data-driven techniques to examine the human, social and cultural impact of the first industrial revolution.”
Smith went on to say: “It is thrilling to bring together this diverse range of experts to work on this important research problem and deliver tools and techniques which will benefit scholars for generations to come.”
Initial research plans involve scientists from The Alan Turing Institute collaborating with curators and researchers to build new software to analyse data drawn initially from millions of pages of out-of-copyright newspaper collections from the British Library.
The resulting new research methods will allow computational linguists and historians to track societal and cultural change in new ways.
The researchers are drawn from the University of Exeter, University of East Anglia, University of Cambridge and Queen Mary, University of London among others.
The lead researcher on the project Dr Ruth Ahnert, who is a senior lecturer in renaissance studies at Queen Mary, University of London, said: “For me this is more than just a research project. It is also a bold proposal for a new research paradigm. That paradigm is defined by radical collaboration that seeks to close the gap between computational sciences and the arts and humanities by creating a space of shared understanding, practices, and norms of publication and communication. We want to create both a data-driven approach to our cultural past, and a human-focused approach to data science.”