Data Repurposing through Compatibility: A Computational Perspective
Abstract
Reuse of data in new contexts beyond the purposes for which it was originally collected has contributed to technological innovation and reducing the consent burden on data subjects. One of the legal mechanisms that makes such reuse possible is purpose compatibility assessment. In this paper, I offer an in-depth analysis of this mechanism through a computational lens. I moreover consider what should qualify as repurposing apart from using data for a completely new task, and argue that typical purpose formulations are an impediment to meaningful repurposing. Overall, the paper positions compatibility assessment as a constructive practice beyond an ineffective standard.
Cite
@article{arxiv.2309.00939,
title = {Data Repurposing through Compatibility: A Computational Perspective},
author = {Asia J. Biega},
journal= {arXiv preprint arXiv:2309.00939},
year = {2023}
}
Comments
To appear in the Special Issue of the Journal of Institutional and Theoretical Economics on "Machine Learning and the Law". Written for the Symposium on Machine Learning and the Law of the Max Planck Institute for Research on Collective Goods: https://www.coll.mpg.de/329557/segovia?c=67659