What would a feminist open source investigation look like?
Co-authored with Gabriela Ivens (Human Rights Watch)
Use of publicly available information to offer radical retellings of violence has powerful democratising potential, both in terms of who contributes to open source investigations and whose stories they centre (Heyns, 2015). At a time when trust in government, media institutions and non-government organisations as fact bearers has been eroded, emergent open source methods have become “an alternative set of truth practices” (Weizman, 2019). Yet there are few accepted guidelines on what is legally, morally, or ethically permissible in such investigations. A growing question within the work of those using open source investigation techniques for human rights is not “Can we do this?” but “Should we be doing this?” What follows is an argument for why intersectional feminist thought should be considered when grappling with the radical possibilities and ethical challenges of open source investigations. The article works through these questions and ideas by giving practical examples of how an investigator might better situate their findings, show their workings, design for ambiguity, practice equity in attribution and find new ways to care for themselves and others.
The article is a direct response to an earlier article by Catherine D’Ignazio titled, “What would feminist data visualization look like?”, which became the academic paper, “Feminist Data Visualization”, co-authored with Lauren F. Klein.
References
Heyns, C., 2015. Report of the Special Rapporteur on Extrajudicial, Summary or Arbitrary Executions.
Weizman, E., 2019. Open Verification. e-flux architecture
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A still from the video ‘Drone Strike in Mir Ali’ showing the witness to the drone strike directing the digital reconstruction of her home. Published on 16 April 2013. Image courtesy of Forensic Architecture, © 2020 Forensic Architecture
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White board with traces of the Civic Laboratory for Environmental Action Research’s approach to equity in author order. Photo by CLEAR, Creative Commons Attribution-ShareAlike 4.0 International License