Title
Conceptualizing Care in the Everyday Work Practices of Machine Learning Developers
Abstract
In this provocation, I investigate machine learning (ML) developers' accounts, which highlight situated, ongoing improvisational work practices that strive to appropriately match datasets, algorithms/modelling techniques, and domain questions. In conceptualizing ML developers' work as practices of care, I provide a case to more closely examine relationships which emerge between local innovations and global regimes of scientific formalization and standardization within sociotechnical systems (in this case, for example, between applied ML projects and scholarly algorithm development). In discussing these local/global relations, this provocation also brings two concepts from the ML field itself to bear (concept drift and transfer learning), productively challenging how we conceptualize everyday technical work ? and the configurative practices of care it includes.
Year
DOI
Venue
2019
10.1145/3301019.3323879
Companion Publication of the 2019 on Designing Interactive Systems Conference 2019 Companion
Keywords
Field
DocType
concept drift, data work, machine learning, practices of care, situated work practices, transfer learning
Human–computer interaction,Engineering,Multimedia
Conference
ISBN
Citations 
PageRank 
978-1-4503-6270-2
0
0.34
References 
Authors
0
1
Name
Order
Citations
PageRank
Christine T. Wolf1406.23