Exploring the Impact of (Not) Changing Default Settings in Algorithmic Crime Mapping - A Case Study of Milwaukee, Wisconsin

MD Romael Haque, Katherine Weathington, Shion Guha
2019 Conference Companion Publication of the 2019 on Computer Supported Cooperative Work and Social Computing - CSCW '19  
Policing decisions, allocations and outcomes are determined by mapping historical crime data geospatially using popular algorithms. In this extended abstract, we present early results from a mixedmethods study of the practices, policies, and perceptions of algorithmic crime mapping in the city of Milwaukee, Wisconsin. We investigate this diferential by visualizing potential demographic biases from publicly available crime data over 12 years
more » ... 2014)(2015)(2016) and conducting semi-structured interviews of 19 city stakeholders and provide future research directions from this study.
doi:10.1145/3311957.3359500 dblp:conf/cscw/HaqueWG19 fatcat:qjvuxjjsprdi7ou2utwg3ckw5e