The Functional Preference of Policemen when Using a Re ection Machine in Preventive Frisking
| dc.contributor.advisor | Haselager, W.F.G. | |
| dc.contributor.advisor | Schraffenberger, Hanna | |
| dc.contributor.author | Venhuizen, Hannah | |
| dc.date.issued | 2022-01-28 | |
| dc.description.abstract | In this thesis we dive into the concept of a Re ection Machine (RM) and the functional preference of policemen interacting with it in a preventive frisking context. An RM is a system which aims to improve the user's decision strategy and enhance their re ection process by questioning the user's decision. Concretely in this thesis, we try to accomplish this by the use of re ective interventions which can be embodied by either questioning or notifying the user about speci c aspects. We implemented a hard-coded version of this conceptual RM in an application simulating a preventive frisking context and used it in an experiment where we questioned the participants about the experience with the RM afterwards. By analyzing this, we show that interventions based on questioning the user's degree of certainty over their decision is experienced as most relevant in general. Furthermore, we argue that we are uncertain about the degree of in uence of a conceptual decision support system on the experience of an RM. Finally, we show that the users generally like the interventions and argue that an RM may be a valuable tool in the police domain. | |
| dc.identifier.uri | https://theses.ubn.ru.nl/handle/123456789/16004 | |
| dc.language.iso | en | |
| dc.thesis.faculty | Faculteit der Sociale Wetenschappen | |
| dc.thesis.specialisation | specialisations::Faculteit der Sociale Wetenschappen::Artificial Intelligence::Bachelor Artificial Intelligence | |
| dc.thesis.studyprogramme | studyprogrammes::Faculteit der Sociale Wetenschappen::Artificial Intelligence | |
| dc.thesis.type | Bachelor | |
| dc.title | The Functional Preference of Policemen when Using a Re ection Machine in Preventive Frisking |
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