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Pretrained AI Models: Performativity, Mobility, and Change
[article]
2019
arXiv
pre-print
The paradigm of pretrained deep learning models has recently emerged in artificial intelligence practice, allowing deployment in numerous societal settings with limited computational resources, but also embedding biases and enabling unintended negative uses. In this paper, we treat pretrained models as objects of study and discuss the ethical impacts of their sociological position. We discuss how pretrained models are developed and compared under the common task framework, but that this may
arXiv:1909.03290v1
fatcat:7doni7tc3rginpokkow2wtiqmy