Computational archival science (CAS) symposium
Monday 20 Jan 2020
Time: 09:30 - 17:00
Bio
Ruth Ahnert is Principal Investigator on the flagship Turing project 'Living With Machines', and a Professor of Literary History and Digital Humanities at Queen Mary University of London. She gained her PhD from the Department of English at the University of Cambridge, but more recently her work has focused on the intersection between literary history and data science. She has held fellowships and grants funded by the AHRC, Stanford Humanities Center, the Folger Shakespeare Library, and the National Endowment of the Humanities (US).
In addition to her Turing-based work she is also Co-I on the AHRC-funded 'Networking the Archives: Assembling and Analysing Early Modern Correspondence'. With Elaine Treharne she is editor of the Stanford University Press book series Stanford Text Technologies.
Research interests
Ruth's research at the Turing is dedicated to the 'Living with Machines' project. This project is a bold proposal for a new research paradigm. In this ground-breaking partnership between the Turing, the British Library, and partner universities (the University of Cambridge, the University of East Anglia, the University of Exeter, and Queen Mary University of London), historians, data scientists, geographers, computational linguists, and curators have been brought together to examine the human impact of industrial revolution.
It is widely recognised that Britain was the birthplace of the world's first industrial revolution, yet there is still much to learn about the human, social, and cultural consequences of this historical moment. Focusing on the long nineteenth century (c.1780-1918), the Living with Machines project aims to harness the combined power of massive digitised archives 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 - the mechanisation of work practices - speaks directly to present debates about how society can accommodate the revolutionary consequences of AI and robotics in what has become known as the fourth industrial revolution. To understand the fraught co-existence of human and machine, this project contends that we need research methods that combine technological innovation and human expertise.
