The ends of data: theories, methods, and interventions in critical data studies

Aim and content

This course is free of charge for PhD students at Danish universities (except Copenhagen Business School), and for PhD Students from NorDoc member faculties. All other participants must pay the course fee.

Anyone can apply for the course, but if you are not a PhD student at a Danish university, you will be placed on the waiting list until enrollment deadline. This also applies to PhD students from NorDoc member faculties. After the enrollment deadline, available seats will be allocated to applicants on the waiting list.

Learning objectives
A student who has met the objectives of the course will be able to:

1. Know contemporary theories dealing with the social lives and afterlives of data

2. Analyze the temporality of valuations and how they interact with conceptions of waste

3. Reflect on and apply selected methods to explore the social lives and afterlives of data

4. Reflect on and intervene in the social lives and afterlives of data

5. Present work describing social, political, economic, environmental, or epistemic aspects of data practices

6. To account for the potential role that the presented theories and methods may play in the student’s own work.

Content
What are the ends of data—meaning, which purposes are they created to serve? And what are the ends of data— meaning, when and how are data permitted to expire, be deleted, or die? This course aims to investigate the intersection of these two questions within data-intensive social practices and infrastructures, where historic data are consistently integrated into new routines, domains and frameworks to address novel inquiries.

Non-utilization of data is often identified as a policy challenge, as a “waste” of data or an untapped potentiality. But what unfolds when the presence of data prompts individuals to develop potential purposes that data might begin to serve, purposes that may differ in radical ways from those for which they were collected? When are data allowed to remain idle and who gets to decide which data to resuscitate and which to terminate? What critical decisions and labour go into repurposing data? And what does it entail to “delete” data in a realm of backups, duplicates, and continual redefinitions of purpose? Can the repercussions of data traces be erased if they have been employed in algorithm training, as currently explored in the field of machine unlearning? Or do data possess an enduring impact on algorithmic processes even after purported deletion? Which ontologies are mobilized to enact the border between data lives, afterlives, and deaths? How do people experience and navigate uncertainties about data deletion and reactivation? How do these uncertainties and transformations shape politics? These are all questions that scholars delving into data-intensive social practices must consider.

This course provides insights into theoretical frameworks, methodologies, and interventions in data practices and processes in a world of waning purpose limitations, leading data to live intricate lives and afterlives. It aims to heighten awareness of the social dynamics of data-intensive practices, encourage reflexivity about methods, and prompt exploration of how studying social practices related to the ends of data can be a form of intervention. Additionally, the course endeavors to enhance students’ abilities to present work on the social, political, economic, or epistemic aspects of data practices in engaging and clear ways. And finally, focusing on the ‘ends’ of data not only emphasizes the ethical considerations surrounding data usage but also draws attention to the potential risks and consequences of data persistence and ephemerality. Understanding data politics through this dual lens provides a more comprehensive view, challenging prevailing assumptions about data’s permanence, thereby enriching existing discourses on data infrastructures, practices, governance and broader socio-political impacts.

The inaugural day of the course will serve as a public seminar where each student delivers a presentation. Students will be assigned commentary roles, and during the following two days of internal course activity, the presentations will be mobilized to explore both presentation formats and content.

The ensuing two course days will consist of a blend of lectures, feedback sessions, and discussions. To successfully complete the course, students are required to present their work and actively participate in discussions regarding the work and the course literature.

Course curriculum
There will be a core curriculum to read before the course including elements of these texts:

Ebeling, Mary F. E. 2022. Afterlives of data: Life and debt under capitalist surveillance (University of California Press: Oakland, California).
Ebeling, Mary FE. 2016. Healthcare and big data. Digital Specters and Phantom Objects (Palgrave Macmillan: New York).
Felt, Ulrike, Susanne Öchsner, and Robin Rae. 2020. ‘The Making of Digital Health: Between Visions and Realizations’, University, Society, Industry, 9: 89-101.
Felt, Ulrike, Susanne Öchsner, Robin Rae, and Ekaterina Osipova. 2023. ‘Doing co-creation: power and critique in the development of a european health data infrastructure’, Journal of Responsible Innovation, 10: 1-21.
Hoeyer, Klaus. 2023. Data Paradoxes. The Politics of Intensified Data Sourcing in Contemporary Healthcare (MIT Press: Cambridge, Massachusetts).
Li, T. C. (2022). Algorithmic Destruction. SMU L. Rev., 75, 479.
Metzler, Ingrid, Lisa-Maria Ferent, and Ulrike Felt. 2023. ‘On samples, data, and their mobility in biobanking: How imagined travels help to relate samples and data’, Big Data & Society, 10: 1-13.
Ratner, Helene, and Evelyn Ruppert. 2019. ‘Producing and projecting data: Aesthetic practices of government data portals’, Big Data & Society, July-December: 1-16.
Ratner, Helene, and Elmholt, Kasper. 2023. ‘Algorithmic constructions of risk: Anticipating uncertain futures in child protection services. Big Data & Society, 10(2). https://doi.org/10.1177/20539517231186120. 1-12
Thylstrup, N. B. (2022). The ethics and politics of data sets in the age of machine learning: Deleting traces and encountering remains. Media, Culture & Society, 44(4), 655-671.
Thylstrup, Nanna Bonde, Kristian Bondo Hansen, Mikkel Flyverbom, and Louise Amoore. 2022. ‘Politics of data reuse in machine learning systems: Theorizing reuse entaglements’, Big Data & Society, 9: 1-10.

An exact curriculum is made available four weeks prior to the course.

Participants
The target group is the PhD student doing work in the area of STS and public health seeking to understand data intensive practices, or students in the areas of critical data studies, sociology of data intensive technologies and work practices, or anthropology of data intensive technologies and work practices. PhD students working in other areas while relying on data-intensive methods may also take this course and use it as a chance to reflect on their own data practices.

Relevance to graduate programmes
The course is relevant to PhD students from the following graduate programmes at the Graduate School of Health and Medical Sciences, UCPH:

Medicine, Culture and Society

Public Health and Epidemiology

Language
English

Form
Students are to submit an abstract for a public seminar and during this seminar present their work. Then they will enter a more regular teaching format where we have lectures from the invited teachers followed by group work and discussions of the literature. We also ask students to provide feedback on each other’s presentations, and discuss presentation formats.

Course director
Klaus Hoeyer, Professor, Centre for Medical STS, Department of Public Health, University of Copenhagen, klho@sund.ku.dk

Teachers
Mary Ebeling, Professor, Drexel University, USA
Ulrike Felt, Professor, University of Vienna, Austria
Nanna Thylstrup, Associate Professor, University of Copenhagen, Denmark
Helene Ratner, Associate Professor, Aarhus University, Denmark

Dates
June 12 from 11:00 to June 14 at 15:00

Course location
University of Copenhagen, KUA, Copenhagen (public seminar, June 12)

AND

University of Copenhagen, Øster Farimagsgade 5, Copenhagen (Internal course, June 13-14).

Registration
Please register before May 1

Expected frequency
This course will only be held once.

Seats to PhD students from other Danish universities will be allocated on a first-come, first-served basis and according to the applicable rules.
Applications from other participants will be considered after the last day of enrolment.

Note: All applicants are asked to submit invoice details in case of no-show, late cancellation or obligation to pay the course fee (typically non-PhD students). If you are a PhD student, your participation in the course must be in agreement with your principal supervisor.

Disclaimer:
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