Re ection machines: an implementation that generates personalized questions based on an o cer's frisking behaviour

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Police policies that include selection procedures based on pro les have in- creasingly been leading to discussions regarding ethnic pro ling, resulting in measures that decrease police autonomy and e ectiveness. This thesis proposes a solution that supports police o cers during a virtual street frisk- ing task by increasing their bias awareness. This is done by implementing a re ection machine, a speci c kind of decision support system. The re ec- tion machine asks personalized questions by monitoring the user's behaviour during the selection procedure and estimating the user's bias. Based on the estimated bias the user receives personalized questions from one of four cat- egories, each category predicting a certain type of bias. The implemented re ection machine is adaptive to the location of the frisking task and pro- duces analyzable output. Whether the implemented re ection machine is e ective in increasing the bias awareness is yet to be determined, but it has proven to be an interesting concept with a lot of room for further research and improvement.
Faculteit der Sociale Wetenschappen