Living with Machines

A five-year research project that will take a fresh look at the well-known history of the Industrial Revolution using data-driven approaches

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Research areas

Data structures Linguistics Research methods Social networks Software framework development Visualisation (Programming languages) Parallel computing Databases Human computer interface Information retrieval Information theory (Applied mathematics) Unsupervised learning Supervised learning Semi-supervised learning Pattern recognition Natural language processing

Introduction

The Alan Turing Institute and the British Library, together with researchers from a range of universities, have been awarded £9.2 million from the UKRI's Strategic Priorities Fund for a major new project. Led by the Arts and Humanities Research Council (AHRC), ‘Living with Machines’ is one of the biggest and most ambitious humanities and science research initiatives ever to launch in the UK.

The project brings together historians, data scientists, geographers, computational linguists, and curators to devise 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 has a particular set of research interests: specifically to examine the ways in which technology altered the lives and culture of people in Britain in the long 19th century (c.1780-1918). The project is marshalling a whole range of sources that have already been digitised from maps, census returns, newspapers, books and journals. While our data is historical, the questions are perhaps never more pertinent as AI is changing the way we live in the 21st century. 

Project aims

Its ten key aims are to:

  • Develop new computational techniques to marshal the UK's rich historical collections to enable new research questions to be posed.
  • Provide new perspectives on the effects of the mechanisation of labour and associated changes on the lives of ordinary people during the long 19th century.
  • Develop generalisable tools, code and infrastructure that can be adapted for and inspire future interdisciplinary research projects.
  • Create new methods for linking heterogenous data sets via toponyms.
  • Deposit enriched and interlinked datasets with the British Library for the use of all.
  • Create computational models to represent how language and meaning changes across time and geography.
  • Develop methods for working with maps and located sources as proxies to understand changes to the industrialising landscape.
  • Develop a coherent set of methods and recommendations for undertaking data-driven research in the current UK context of mixed-rights data access.
  • Build UK capacity in digital humanities through the development of tutorials and code to facilitate the research of the broader community.
  • Generate research breakthroughs to maintain UK global leadership in digital humanities and drive large-scale international partnerships and opportunities.

Applications

The research methodologies and tools developed as a result of the project are transforming how researchers can access and understand digitised historic collections. We offer not only a host of new software and methods for wrangling this data, but examples of how this changes the history we can tell. Find out more about software and methods.

Furthermore, we have sought to lower the bar to others trying to do this work in future in our forthcoming book Collaborative Historical Research in the Age of Big Data (Cambridge University Press, November 2022). The book discusses not only how to set up an interdisciplinary collaborative team, but also takes readers through the steps of getting hold of cultural heritage data and the infrastructure required. While it suggests a set of pragmatic strategies that projects can employ it also highlights some key structural issues that can only be addressed by a rethink of national policy and funding priorities in the UK. 
 

Publications

Books

Ahnert, Ruth, et al. Collaborative Historical Research in the Age of Big Data. Cambridge University Press, Available Open Access.

Most recent articles, book chapters and conferences

Ardanuy, Mariona Coll, et al. “Resolving Places, Past and Present: Toponym Resolution in Historical British Newspapers Using Multiple Resources.” Proceedings of the 13th Workshop on Geographic Information Retrieval, Association for Computing Machinery, 2019, pp. 1–6.

Arenas, Diego, et al. Design Choices for Productive, Secure, Data-Intensive Research at Scale in the Cloud. arXiv:1908.08737, arXiv, 15 Sept. 2019.

Beelen, Kaspar, Jon Lawrence, Daniel C. S. Wilson, and David Beavan. “Bias and Representativeness in Digitized Newspaper Collections: Introducing the Environmental Scan.” Digital Scholarship in the Humanities, July 2022, p. fqac037.

Beelen, Kaspar, Ruth Ahnert, David Beavan, Mariona Coll Ardanuy, Kasra Hosseini, et al. Contextualizing Victorian Newspapers.

Beelen, Kaspar, Ruth Ahnert, David Beavan, Mariona Coll Ardanuy, Emma Griffin, et al. Living with Machines: Exploring Bias in the British Newspaper Archive.

Beelen, Kaspar, Federico Nanni, Mariona Coll Ardanuy, Kasra Hosseini, et al. “When Time Makes Sense: A Historically-Aware Approach to Targeted Sense Disambiguation.” Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, Association for Computational Linguistics, 2021, pp. 2751–61.

Boyd Davis, Stephen, et al. “Can I Believe What I See? Data Visualization and Trust in the Humanities.” Interdisciplinary Science Reviews, vol. 46, no. 4, Oct. 2021, pp. 522–46.

Coll Ardanuy, Mariona, Kasra Hosseini, et al. A Deep Learning Approach to Geographical Candidate Selection through Toponym Matching.

Coll Ardanuy, Mariona, Federico Nanni, et al. “Living Machines: A Study of Atypical Animacy.” Proceedings of the 28th International Conference on Computational Linguistics, International Committee on Computational Linguistics, 2020, pp. 4534–45.

Coll Ardanuy, Mariona, Kaspar Beelen, et al. “Station to Station: Linking and Enriching Historical British Railway Data.” Proceedings of the Conference on Computational Humanities Research 2021, Proceedings of the Conference on Computational Humanities Research 2021.

View all Living with Machines publications

Recent updates

February 2023

Publication of the Living with Machines book on data, infrastructure, and collaboration

We are delighted to share with you Open Access our book ‘Collaborative Historical Research in the Age of Big Data: Lessons from an interdisciplinary project’, published by Cambridge University Press, as part of the series Elements. Co-authored by Ruth Ahnert, Emma Griffin, Mia Ridge, Giorgia Tolfo, and the LWM team, the book addresses the challenges of establishing and managing a truly multidisciplinary digital humanities project in the complex landscape of cultural data in the UK. In contrast to many previous digital humanities projects which have sought to create resources, the project was concerned to work with what was already there, by leveraging more than twenty-years' worth of digitisation projects in order to deepen our understanding of the impact of mechanisation on nineteenth-century Britain. Sharing our experience, we hope to provide tools and methods for future researchers seeking to undertake digital history projects.

The book launch will take place online on 7th March 2023, 5PM GMT, as part of AI UK Fringe Events. Register here.

 

Living with Machines exhibition 

The exhibition ‘Living with Machines’, co-curated by the British Library and Leeds City Museum, and inspired by the Living with Machines research project, opened on July 29, 2022 and concluded on January 8, 2023 at Leeds City Museum.

The Living with Machines exhibition revealed surprising parallels between the Industrial Revolution and today’s world of ‘big tech’, from the origins of football leagues and fast fashion to the 9-to-5 working day. The exhibition reached more than 42,000 visitors in total.

Find out more about the exhibition and related events

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Research Engineering

The research engineering groups from the Turing and British Library are developing new cutting-edge research methods blending data science and digital humanities, in collaboration with linguists and historians. These range from developing methods to query terabytes of unstructured data, to designing deep learning techniques able to identify individuals and extract their life story from multiple sources of data, spanning decades.

While underpinning research through infrastructure, the Research Engineering Group is also inspiring new questions to be asked at a hitherto unprecedented scale in the humanities.

View the Research Engineering page