Skip to main content

Department of Management

Dr Hugh Williamson

Dr Hugh Williamson

Research Fellow

 H.Williamson@exeter.ac.uk

 


Overview

Social anthropologist and science and technology studies researcher, focused on agriculture, the biosciences (plant and animal biology) and data and digital technology. Ethnographic research on rural transformation in Romania and Eastern Europe.

I am currently Research Fellow in responsible innovation in digital agriculture as part of DIGIT Lab (Business School, University of Exeter). In this role, I am looking at the use of digital technologies and data in animal agriculture in the U.K.

Biography

I hold a BA in Anthropology from Durham University (2013), an interdisciplinary course which encompassed anthropology's social, medical and biological subfields. I subsequently studied at the University of Cambridge, where I received an MRes (2014) and PhD (2018) in Social Anthropology. At Exeter, I previously held the position of Research Fellow on the Alan Turing Institute-funded project ‘From Field Data to Global Indicators: Towards a Framework for Intelligent Plant Data Linkage’ (2019-2022), based at Egenis, the Centre for the Study of the Life Sciences.

Research interests:

  • Plant, agricultural and ecological sciences
  • Plant and animal breeding and biotechnology
  • Quantitative genetics and its interaction with new data technologies
  • Agroecological conservation, rural development and participatory methodologies
  • Governance of science and common resources in a transnational context
  • Romania and post-socialist Europe 

Open access volume Towards Responsible Plant Data Linkage: Data Challenges for Agricultural Research and Development, co-edited with Sabina Leonelli, out now with Springer.

Links

Back to top


Research

Research interests

I am an anthropologist of digital technology and data use in agriculture and the biosciences, especially plant and animal biology for agricultural uses. I have also conducted ethnographic research on rural politics in Romania, and have a broader interest in rural transformations in post-socialist Eastern Europe and Asia.

My work draws on science and technology studies (STS) and philosophy of science to understand the social shaping of science and technologies, their societal implications, and questions of best practice and responsible practice. In recent years I have conducted qualitative research on how data circulates and is governed in plant biology and agricultural science, and its implications for agricultural development.

I am especially interested in the intersection of older traditions of quantitative genetics with new techniques for data collection and analysis in plant and animal breeding, and how these seemingly mundane technologies are contributing to significant shifts in the scale, pace and organisation of breeding. I am also interested in new methods of data-driven environmental characterisation and classification in the plant sciences, their implications for adapting agriculture to climate change, and their intersection with agroecology and sustainable agriculture movements. In addition, I have conducted work on the challenges and opportunities facing the implementation of AI and machine learning in plant biology and agriculture.

Previously, I have conducted ethnographic fieldwork in an agroecological conservation zone in Transylvania, Romania, looking at dynamics of rural development and cultural politics. This research focused especially on how younger Romanians were navigating social, technical and economic changes in the countryside relative to Romania’s post-socialist transition and entry into the European Union. I retain a significant interest in rural transformation in the region, including in neighbouring former Soviet states such as Moldova and Ukraine relative to ongoing political events.

Back to top


Publications

Books

Choudhary A, Fox G, Hey T (2022). Artificial Intelligence for Science., WORLD SCIENTIFIC.
Williamson HF, Leonelli S (2022). Towards Responsible Plant Data Linkage: Data Challenges for Agricultural Research and Development., Springer. Abstract.

Journal articles

Williamson HF, Brettschneider J, Caccamo M, Davey RP, Goble C, Kersey PJ, May S, Morris RJ, Ostler R, Pridmore T, et al (2023). Data management challenges for artificial intelligence in plant and agricultural research. F1000Research, 10, 324-324. Abstract.
Williamson HF, Leonelli S (2022). Accelerating agriculture: Data-intensive plant breeding and the use of genetic gain as an indicator for agricultural research and development. Studies in History and Philosophy of Science, 95, 167-176.
Williamson HF, Brettschneider J, Caccamo M, Davey RP, Goble C, Kersey PJ, May S, Morris RJ, Ostler R, Pridmore T, et al (2021). Data management challenges for artificial intelligence in plant and agricultural research. F1000Research, 10, 324-324. Abstract.
Williamson HF, Brettschneider J, Caccamo M, Davey RP, Goble C, Kersey PJ, May S, Morris RJ, Ostler R, Pridmore T, et al (2021). Data management challenges for artificial intelligence in plant and agricultural research. F1000Research, 10 Abstract.
Fedirko T, Samanani F, Williamson HF (2021). Grammars of liberalism. Social Anthropology, 29(2), 373-386.

Chapters

Williamson H, Leonelli S (2023). Cultivating Responsible Plant Breeding Strategies: Conceptual and Normative Commitments in Data-Intensive Agriculture. In Williamson H, Leonelli S (Eds.) Towards Responsible Plant Data Linkage: Data Challenges for Agricultural Research and Development, Springer.
Leonelli S, Williamson H (2023). Introduction: Towards Responsible Plant Data Linkage. In Williamson H, Leonelli S (Eds.) Towards Responsible Plant Data Linkage: Data Challenges for Agricultural Research and Development, Springer.
Leonelli S, Williamson H (2022). Artificial Intelligence in Plant and Agricultural Research. In Choudhary A, Fox G, Het T (Eds.) AI for Science, World Scientific Publishers. Abstract.

Back to top


Edit Profile