The Values Encoded in Machine Learning Research

University College Dublin · Stanford University · +3 more institutions

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Abstract

Machine learning currently exerts an outsized influence on the world, increasingly affecting institutional practices and impacted communities. It is therefore critical that we question vague conceptions of the field as value-neutral or universally beneficial, and investigate what specific values the field is advancing. In this paper, we first introduce a method and annotation scheme for studying the values encoded in documents such as research papers. Applying the scheme, we analyze 100 highly cited machine learning papers published at premier machine learning conferences, ICML and NeurIPS. We annotate key features of papers which reveal their values: their justification for their choice of project, which…

Citation impact

271
total citations
FWCI
22.60
Percentile
100%
References
74
Citations per year

Authors

6

Topics & keywords

Keywords
  • Operationalization
  • Novelty
  • Computer science
  • Field (mathematics)
  • Artificial intelligence
  • Value (mathematics)
  • Data science
  • Annotation
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