Living with Machines

The storage void of the new British Library National Newspaper Building
The storage void of the new British Library National Newspaper Building at Boston Spa in West Yorkshire.

A research project combining digital archives with data science techniques to investigate the effects of mechanisation on society

Published date:

About

Living with Machines is a major new five year inter-disciplinary research project using ‘radically collaborative’ methods to analyse digital sources at scale to provide new insights into the human impact of the industrial revolution. Living with Machines will see curators, data scientists, historians, geographers and computational linguists working together to devise new methods in data science and artificial intelligence to revolutionise the way historical sources are analysed, and provide vital insight into the debates and discussions taking place in response to today’s digitally-inspired revolutions.

Project Partners

Alan Turing Institute, the British Library, and the University of Cambridge, the University of East Anglia, the University of Exeter, and Queen Mary University of London.

Aims of the project

In recognition of the significant changes currently underway in technology, notably in artificial intelligence, the project will use the century following the first Industrial Revolution, and the changes brought about by the advance of technology across all aspects of society during c.1780-1918, as its focus point.

The project aims to harness the combined power of massive digitised historical documents and computational analytical tools to examine the ways in which technology altered the very fabric of human existence on a hitherto unprecedented scale. The central theme speaks directly to present debates about how contemporary society can accommodate the revolutionary consequences of AI and robotics.

Living with Machines will lead the research and development of new ways to marshal the UK’s growing number of digitised historical texts and documents. The creation of innovative computational models, tools, code, and infrastructure will be key to enabling new scholarly questions with new depths of inquiry. This will act as a catalyst for other research projects, encouraging them to export high performance computing and big data to new domains of research.

Key starting points for the project include marshaling data, developing workflows and methods for ensuring data quality developing intuitive interfaces to facilitate collaboration with historians, and the launch of the collaborative research agenda through project ‘laboratories’. There will be future calls and opportunities for researchers to get involved.