Keeping Community in the Loop: Understanding Wikipedia Stakeholder Values for Machine Learning-Based Systems

@article{Smith2020KeepingCI,
  title={Keeping Community in the Loop: Understanding Wikipedia Stakeholder Values for Machine Learning-Based Systems},
  author={C. Estelle Smith and Bowen Yu and Anjali Srivastava and Aaron Halfaker and Loren Terveen and Haiyi Zhu},
  journal={Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems},
  year={2020}
}
  • C. Estelle Smith, Bowen Yu, +3 authors Haiyi Zhu
  • Published 2020
  • Computer Science
  • Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems
  • On Wikipedia, sophisticated algorithmic tools are used to assess the quality of edits and take corrective actions. However, algorithms can fail to solve the problems they were designed for if they conflict with the values of communities who use them. In this study, we take a Value-Sensitive Algorithm Design approach to understanding a community-created and -maintained machine learning-based algorithm called the Objective Revision Evaluation System (ORES)---a quality prediction system used in… CONTINUE READING

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