Machine learning for policing: a case study on arrests in Chile

Simple item page
dc.catalogadorgjm
dc.contributor.authorWout, Elwin van't
dc.contributor.authorPieringer Baeza, Christian Philip
dc.contributor.authorTorres Irribarra, David
dc.contributor.authorAsahi Kodama, Kenzo Javier
dc.contributor.authorLarroulet Philippi, Pilar
dc.contributor.otherCEDEUS (Chile)
dc.date.accessioned2024-09-27T13:27:30Z
dc.date.available2024-09-27T13:27:30Z
dc.date.issued2020
dc.description.abstractPolice agencies expend considerable effort to anticipate future incidences of criminal behaviour. Since a large proportion of crimes are committed by a small group of individuals, preventive measures are often targeted on prolific offenders. There is a long-standing expectation that new technologies can improve the accurate identification of crime patterns. Here, we explore big data technology and design a machine learning algorithm for forecasting repeated arrests. The forecasts are based on administrative data provided by the national Chilean police agencies, including a history of arrests in Santiago de Chile and personal metadata such as gender and age. Excellent algorithmic performance was achieved with various supervised machine learning techniques. Still, there are many challenges regarding the design of the mathematical model, and its eventual incorporation into predictive policing will depend upon better insights into the effectiveness and ethics of preemptive strategies.
dc.description.funderCentre for Public Policies, Pontificia Universidad Catolica de Chile
dc.description.funderFONDECYT
dc.description.funderCEDEUS, ANID/FONDAP
dc.format.extent16 páginas
dc.fuente.origenWOS
dc.identifier.doi10.1080/10439463.2020.1779270
dc.identifier.eissn1477-2728
dc.identifier.issn1043-9463
dc.identifier.scopusid2-s2.0-85087112163
dc.identifier.urihttps://doi.org/10.1080/10439463.2020.1779270
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/87993
dc.identifier.wosidWOS:000545817100001
dc.information.autorucEscuela de Ingenería; Wout, Elwin van't; S/I; 1024024
dc.information.autorucEscuela de Ingeniería; Pieringer Baeza, Christian Philip; 0000-0003-2486-6733; 169967
dc.information.autorucEscuela de Psicología; Torres Irribarra, David; 0009-0007-4686-5279; 120988
dc.information.autorucEscuela de Ingeniería; Asahi Kodama, Kenzo Javier; 0000-0001-7838-4647; 4661
dc.information.autorucInstituto de Sociología; Larroulet Philippi, Pilar; 0000-0002-8268-8122; 17591
dc.issue.numero9
dc.language.isoen
dc.nota.accesocontenido parcial
dc.pagina.final1050
dc.pagina.inicio1036
dc.revistaPolicing and Society
dc.rightsacceso restringido
dc.subjectData analytics
dc.subjectRepeated arrests
dc.subjectPredictive policing
dc.subject.ddc600
dc.subject.deweyTecnologíaes_ES
dc.subject.ods05 Gender equality
dc.subject.odspa05 Igualdad de género
dc.titleMachine learning for policing: a case study on arrests in Chile
dc.typeartículo
dc.volumen31
sipa.codpersvinculados1024024
sipa.codpersvinculados169967
sipa.codpersvinculados120988
sipa.codpersvinculados4661
sipa.codpersvinculados17591
sipa.trazabilidadWOS;05-06-2021
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Police agencies expend considerable effort to anticipate fut.pdf
Size:
204.4 KB
Format:
Adobe Portable Document Format
Description:
Download
Collections
Artículos de revistas
CEDEUS