Automatic Classifiers as Scientific Instruments: One Step Further Away from Ground-Truth

@inproceedings{Whitehill2018AutomaticCA,
  title={Automatic Classifiers as Scientific Instruments: One Step Further Away from Ground-Truth},
  author={Jacob Whitehill and Anand Ramakrishnan},
  booktitle={ICML},
  year={2018}
}
Automatic machine learning-based detectors of various psychological and social phenomena (e.g., emotion, stress, engagement) have great potential to advance basic science. However, when a detector $d$ is trained to approximate an existing measurement tool (e.g., a questionnaire, observation protocol), then care must be taken when interpreting measurements collected using $d$ since they are one step further removed from the underlying construct. We examine how the accuracy of $d$, as quantified… CONTINUE READING

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