@inproceedings{weathingtonHarmDataScience,
  title = {Harm and {{Data Science}}: {{Framing Negative Human Outcomes}} as a {{Data Science Problem}}},
  booktitle = {{{CSCW Workshop}} on {{Interrogating Data Science}}},
  author = {Weathington, Katherine and Scheuerman, Morgan Klaus},
  year = 2020,
  month = oct,
  abstract = {After researching predictive policing practices, and with police violence an ever present horror, the first author found herself motivated to consider the real human harm that can result from data driven decisions. We examine how certain data science practices associated with predictive policing contribute to and are complicit with human suffering caused by police brutality. We then put forward an idea of data scientists internally motivated to center their work around minimizing negative human consequences rather than traditional goals of performance optimization or increasing profits. We encourage further research into the disciplinary norms which distance model builders from practical implementations of their work, and how academics can intervene.},
  langid = {english},
  file = {/Users/Morgan.Scheuerman/Zotero/storage/A2ZG7WJT/Weathington and Scheuerman - Harm and Data Science Framing Negative Human Outcomes as a Data Science Problem.pdf}
}