Corpus ID: 218665237

Participatory Problem Formulation for Fairer Machine Learning Through Community Based System Dynamics

@article{Martin2020ParticipatoryPF,
  title={Participatory Problem Formulation for Fairer Machine Learning Through Community Based System Dynamics},
  author={Donald Martin and V. Prabhakaran and Jill A. Kuhlberg and A. Smart and William S. Isaac},
  journal={ArXiv},
  year={2020},
  volume={abs/2005.07572}
}
Recent research on algorithmic fairness has highlighted that the problem formulation phase of ML system development can be a key source of bias that has significant downstream impacts on ML system fairness outcomes. However, very little attention has been paid to methods for improving the fairness efficacy of this critical phase of ML system development. Current practice neither accounts for the dynamic complexity of high-stakes domains nor incorporates the perspectives of vulnerable… Expand
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