Data Ownership: Concepts | Analysis | Critique

Description

Data Ownership Workshop

Convened by Amira Moeding (Cambridge University), Jan Beuerbach (University of Leipzig), Birte de Gruisbourne (Paderborn University), Tobias Stadler (University of Oldenburg)

As more and more data are generated and collected by individuals and organisations, questions around data ownership and control are becoming increasingly urgent. Not only because the economic value of data as an asset drives current business models but also because legal, ethical, and societal implications of data practices raise questions on reliability, responsibility and relationality.

At the moment, one can see a tension play out between data that is accessible via the internet and hence can be scraped to build so-called ‘artificial intelligence’ applications or tools that are then often protected as intellectual property, data collected by states, and privatised data accumulated by private companies. The European Union filing a lawsuit against ChatGPT is just the latest instance of many legal battles and questions surrounding legitimate data ownership.

We want to illuminate this tension and consider the different forms of data ownership, privatisation and accumulation currently promoted by ‘Big Tech’ companies. By focusing on the questions of data ownership and governance, we hope also to open up questions on the practices of data production, evaluation, valorisation and use.

We draw on different theories and methods of critique to analyse current practices of data production and use, to gain a clear understanding of how data are privatised and accumulated as property, as well as dynamics of expropriation, subjectivation and colonialism that result from the idea often promoted by industry actors that there is ‘no data like more data’.

As we inquire into the ontologies of data and the new epistemological virtues established by so-called large models, we draw on methods of historical enquiry but also data literacy when reflecting on the criticisms against ‘Big Data’ often launched from feminist, post-colonial, or racialised perspectives towards more careful practices of data generation.

We hope to connect these methods more explicitly to critical theory perspectives on data generation as labour and the valorisation of data through industry practices. We welcome expressions of interest from scholars at any stage of their careers by June 30. Please include your name, affiliation, and area of research in the email and send to Amira (alam2@cam.ac.uk), Jan (jan.beuerbach@uni-leipzig.de), Birte (birte.de.gruisbourne@uni-paderborn.de) or Tobias (tobias.stadler@uni-oldenburg.de)

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