Call for abstracts for public seminar the ends of data theories, methods, and interventions in critical data and AI studies
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 symposium investigates the intersection of these two questions within data-intensive social practices and infrastructures, where historical 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 destroying or repurposing data? And what does it entail to "delete" data in a realm of backups, duplicates, and continual redefinitions of purpose?
Moreover, emergent forms of algorithmic systems also pose epistemological and ontological nature: 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? And how do people and politics navigate and shape uncertainties about data deletion and reactivation?
These are all questions that scholars delving into data-intensive social practices must consider.
Important information
Participation is conditioned upon acceptance of abstract. We welcome abstract submissions that examine the multiple ends of data from emergent and established fields including, but not limited to, STS, critical data and AI studies, history of science, digital culture and platform studies, critical archival and information studies and communication studies
- Abstract length: max 300 words
- Abstract deadline: May 1st
This event is part of a PhD Course of the same name: Graduate School of health and Medical Sciences (ku.dk). Students who wish to join the course are guaranteed acceptance of the paper and can present. Deadline: May 1st.