A model to improve the Evaluation and Selection of Public Contest´s Candidates (Police Officers) based on AI technologies
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10362/145530 |
Resumo: | Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Business Analytics |
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A model to improve the Evaluation and Selection of Public Contest´s Candidates (Police Officers) based on AI technologiesArtificial IntelligenceSentiment AnalysisFacial RecognitionPolice ForcesTransparencyDesign Science Research (DSR)Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Business AnalyticsThe number of candidates applying to Public Contests is increasing compared to the number of Human Resources employees required for selecting them for Police Forces. This work intends to perceive how those Public Institutions can evaluate and select their candidates efficiently during the different phases of the recruitment process, and for achieving this purpose AI approaches will be studied. This paper presents two research questions and introduces a corresponding systematic literature review, focusing on AI technologies, so the reader is able to understand which are most used and more appropriate to be applied to Police Forces as a complementary recruitment strategy of the National Criminal Investigation Police agency of Portugal – Polícia Judiciária. Design Science Research (DSR) was the methodological approach chosen. The suggestion of a theoretical framework is the main contribution of this study in pair with the segmentation of the candidates (future Criminal Inspectors). It also helped to comprehend the most important facts facing Public Institutions regarding the usage of AI technologies, to make decisions about evaluating and selecting candidates. Following the PRISMA methodology guidelines, a systematic literature review and meta-analyses method was adopted to identify how can the usage and exploitation of transparent AI have a positive impact on the recruitment process of a Public Institution, resulting in an analysis of 34 papers published between 2017 and 2021. The AI-based theoretical framework, applicable within the analysis of literature papers, solves the problem of how the Institutions can gain insights about their candidates while profiling them; how to obtain more accurate information from the interview phase; and how to reach a more rigorous assessment of their emotional intelligence providing a better alignment of moral values. This way, this work aims to advise the improvement of the decision making to be taken by a recruiter of a Police Force Institution, turning it into a more automated and evidence-based decision when it comes to recruiting the adequate candidate for the place.Santos, Vitor Manuel Pereira Duarte dosAnastasiadou, MariaRUNGonçalves, Mariana Bailão2022-11-15T16:12:32Z2022-10-252022-10-25T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/145530TID:203097858enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:26:02Zoai:run.unl.pt:10362/145530Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:52:08.103814Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
A model to improve the Evaluation and Selection of Public Contest´s Candidates (Police Officers) based on AI technologies |
title |
A model to improve the Evaluation and Selection of Public Contest´s Candidates (Police Officers) based on AI technologies |
spellingShingle |
A model to improve the Evaluation and Selection of Public Contest´s Candidates (Police Officers) based on AI technologies Gonçalves, Mariana Bailão Artificial Intelligence Sentiment Analysis Facial Recognition Police Forces Transparency Design Science Research (DSR) |
title_short |
A model to improve the Evaluation and Selection of Public Contest´s Candidates (Police Officers) based on AI technologies |
title_full |
A model to improve the Evaluation and Selection of Public Contest´s Candidates (Police Officers) based on AI technologies |
title_fullStr |
A model to improve the Evaluation and Selection of Public Contest´s Candidates (Police Officers) based on AI technologies |
title_full_unstemmed |
A model to improve the Evaluation and Selection of Public Contest´s Candidates (Police Officers) based on AI technologies |
title_sort |
A model to improve the Evaluation and Selection of Public Contest´s Candidates (Police Officers) based on AI technologies |
author |
Gonçalves, Mariana Bailão |
author_facet |
Gonçalves, Mariana Bailão |
author_role |
author |
dc.contributor.none.fl_str_mv |
Santos, Vitor Manuel Pereira Duarte dos Anastasiadou, Maria RUN |
dc.contributor.author.fl_str_mv |
Gonçalves, Mariana Bailão |
dc.subject.por.fl_str_mv |
Artificial Intelligence Sentiment Analysis Facial Recognition Police Forces Transparency Design Science Research (DSR) |
topic |
Artificial Intelligence Sentiment Analysis Facial Recognition Police Forces Transparency Design Science Research (DSR) |
description |
Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Business Analytics |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-11-15T16:12:32Z 2022-10-25 2022-10-25T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10362/145530 TID:203097858 |
url |
http://hdl.handle.net/10362/145530 |
identifier_str_mv |
TID:203097858 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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