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AI and public contests

2022-10-18Artigo científico Acesso aberto
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dc.contributor.authorGoncalves, Mariana Bailao
dc.contributor.authorAnastasiadou, Maria
dc.contributor.authorSantos, Vitor
dc.contributor.institutionNOVA Information Management School (NOVA IMS)
dc.contributor.institutionInformation Management Research Center (MagIC) - NOVA Information Management School
dc.contributor.pblAssociação Portuguesa para o Estudo do Quaternário (APEQ)
dc.date.accessioned2022-09-28T22:49:18Z
dc.date.available2022-09-28T22:49:18Z
dc.date.issued2022-10-18
dc.descriptionGoncalves, M. B., Anastasiadou, M., & Santos, V. (2022). AI and public contests: a model to improve the evaluation and selection of public contest candidates in the Police Force. Transforming Government: People, Process and Policy, 16(4), 22. https://doi.org/10.1108/TG-05-2022-0078 ---%ABS2%---Funding: This work was supported by national funds through FCT (Fundação para a Ciência e a Tecnologia), under the project – UIDB/04152/2020 – Centro de Investigação em Gestão de Informação (MagIC)/NOVA IMS.
dc.description.abstractAbstract Purpose The number of candidates applying to public contests (PC) is increasing compared to the number of human resources employees required for selecting them for the Police Force (PF). This work intends to perceive how those public institutions can evaluate and select their candidates efficiently during the different phases of the recruitment process. To achieve this purpose, artificial intelligence (AI) was studied. This paper aims to focus on analysing the AI technologies most used and appropriate to the PF as a complementary recruitment strategy of the National Criminal Investigation police agency of Portugal – Polícia Judiciária. Design/methodology/approach Using design science research as a methodological approach, the authors suggest a theoretical framework in pair with the segmentation of the candidates and comprehend the most important facts facing public institutions regarding the usage of AI technologies to make decisions about evaluating and selecting candidates. Following the preferred reporting items for systematic reviews and meta-analyses methodology guidelines, a systematic literature review and meta-analyses method was adopted to identify how the usage and exploitation of transparent AI positively impact the recruitment process of a public institution, resulting in an analysis of 34 papers between 2017 and 2021. Findings Results suggest that the conceptual pairing of evaluation and selection problems of candidates who apply to PC with applicable AI technology such as K-means, hierarchical clustering, artificial neural network and convolutional neural network algorithms can support the recruitment process and could help reduce the workload in the entire process while maintaining the standard of responsibility. The combination of AI and human decision-making is a fair, objective and unbiased process emphasising a decision-making process free of nepotism and favouritism when carefully developed. Innovative and modern as a category, group the statements that emphasise the innovative and contemporary nature of the process. Research limitations/implications There are two main limitations in this study that should be considered. Firstly, the difficulty regarding the timetable, privacy and legal issues associated with public institutions. Secondly, a small group of experts served as the validation group for the new framework. Individual semi-structured interviews were conducted to alleviate this constraint. They provide additional insights into an interviewee’s opinions and beliefs. Social implications Ensure that the system is fair, transparent and facilitates their application process. Originality/value The main contribution is the AI-based theoretical framework, applicable within the analysis of literature papers, focusing on 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 work aims to improve the decision-making process of a PF institution recruiter by turning it into a more automated and evidence-based decision when recruiting an adequate candidate for the job vacancy.en
dc.description.versionauthorsversion
dc.description.versionpublished
dc.format.extent627
dc.format.extent1388789
dc.identifier.doi10.1108/TG-05-2022-0078
dc.identifier.issn1750-6166
dc.identifier.otherPURE: 46765320
dc.identifier.otherPURE UUID: 376dcf69-11f6-45f8-b7b5-4aad6813edcb
dc.identifier.othercrossref: 10.1108/TG-05-2022-0078
dc.identifier.otherScopus: 85138863281
dc.identifier.otherWOS: 000858161300001
dc.identifier.otherORCID: /0000-0002-4223-7079/work/119792611
dc.identifier.otherORCID: /0000-0003-2770-7025/work/215175648
dc.identifier.urihttp://hdl.handle.net/10362/144373
dc.identifier.urlhttps://www.scopus.com/pages/publications/85138863281
dc.identifier.urlhttps://www.webofscience.com/wos/woscc/full-record/WOS:000858161300001
dc.identifier.urlhttps://www.emerald.com/insight/content/doi/10.1108/TG-05-2022-0078/full/html
dc.language.isoeng
dc.peerreviewedyes
dc.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04152%2F2020/PT
dc.relationInformation Management Research Center
dc.subjectArtificial intelligence
dc.subjectSentiment analysis
dc.subjectFacial recognition
dc.subjectPolice force
dc.subjectTransparency
dc.subjectDesign science research
dc.subjectPublic Administration
dc.subjectComputer Science Applications
dc.subjectInformation Systems and Management
dc.subjectSDG 16 - Peace, Justice and Strong Institutions
dc.titleAI and public contestsen
dc.title.subtitlea model to improve the evaluation and selection of public contest candidates in the Police Forceen
dc.typejournal article
degois.publication.firstPage
degois.publication.issue4
degois.publication.lastPage
degois.publication.titleTransforming Government: People, Process and Policy
degois.publication.volume16
dspace.entity.typePublication
oaire.awardNumberUIDB/04152/2020
oaire.awardTitleInformation Management Research Center
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04152%2F2020/PT
oaire.fundingStream6817 - DCRRNI ID
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccess
relation.isProjectOfPublication3274bdb3-4dd3-4bbe-8f74-d34190081f87
relation.isProjectOfPublication.latestForDiscovery3274bdb3-4dd3-4bbe-8f74-d34190081f87

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NIMS: MagIC - Artigos em revista internacional com arbitragem científica (Peer-Review articles in international journals)