PredPol perpetuates racial, ethnic, income bias
A n investigation by The Markup and Gizmodo discovered p otential bias issues with crime prediction system PredPol. Analysis of a huge volume of crime predictions left on an unsecured server showed PredPol (now renamed Geolitica) often avoided White and middle-to-upper-income residents neighbourhoods, and targeted Black and Latino neighbourhoods. The findings suggest PredPol technology is resulting in so-called 'feedback loops' in which lower-income, ethnic zones are treated as surveillance hotspots and lead to disproportionately higher numbers of arrests of minority populations. System 🤖 PredPol (Geolitica) website PredPol Wikipedia profile Operator: Los Angeles Police Department Developer: Geolitica/PredPol Country: USA Sector: Govt - police Purpose: Predict crime Technology: Behavioural analysis Issue: Accuracy/reliability; Bias/discrimination - race, ethnicity, income Investigations, assessments, audits 🧐 The MarkUp (2021). Crime Prediction Software Promised to Be Free of Biases. New Data Shows It Perpetuates Them The MarkUp (2021). How We Determined Crime Prediction Software Disproportionately Targeted Low-Income, Black, and Latino Neighborhoods The MarkUp (2021). PredPol investigation data
- Date it happened
- 2021-12-01
- Organisation involved
- Los Angeles Police Department
- Product, system or model
- PredPol
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