Objective and bias-free measures of candidate motivation during job applications

Abstract Society suffers from biases and discrimination, a longstanding dilemma that stems from ungrounded, subjective judgments. Especially unequal opportunities in labor remain a persistent challenge, despite the recent inauguration of top-down diplomatic measures. Here we propose a solution by us...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Mitchel Kappen, Marnix Naber
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/7b3ae15bfbce4308b5db649d49b7a793
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:7b3ae15bfbce4308b5db649d49b7a793
record_format	dspace
spelling	oai:doaj.org-article:7b3ae15bfbce4308b5db649d49b7a7932021-11-14T12:23:24ZObjective and bias-free measures of candidate motivation during job applications10.1038/s41598-021-00659-y2045-2322https://doaj.org/article/7b3ae15bfbce4308b5db649d49b7a7932021-11-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-00659-yhttps://doaj.org/toc/2045-2322Abstract Society suffers from biases and discrimination, a longstanding dilemma that stems from ungrounded, subjective judgments. Especially unequal opportunities in labor remain a persistent challenge, despite the recent inauguration of top-down diplomatic measures. Here we propose a solution by using an objective approach to the measurement of nonverbal behaviors of job candidates that trained for a job assessment. First, we implemented and developed artificial intelligence, computer vision, and unbiased machine learning software to automatically detect facial muscle activity and emotional expressions to predict the candidates’ self-reported motivation levels. The motivation judgments by our model outperformed recruiters’ unreliable, invalid, and sometimes biased judgments. These findings mark the necessity and usefulness of novel, bias-free, and scientific approaches to candidate and employee screening and selection procedures in recruitment and human resources.Mitchel KappenMarnix NaberNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-8 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Mitchel Kappen Marnix Naber Objective and bias-free measures of candidate motivation during job applications
description	Abstract Society suffers from biases and discrimination, a longstanding dilemma that stems from ungrounded, subjective judgments. Especially unequal opportunities in labor remain a persistent challenge, despite the recent inauguration of top-down diplomatic measures. Here we propose a solution by using an objective approach to the measurement of nonverbal behaviors of job candidates that trained for a job assessment. First, we implemented and developed artificial intelligence, computer vision, and unbiased machine learning software to automatically detect facial muscle activity and emotional expressions to predict the candidates’ self-reported motivation levels. The motivation judgments by our model outperformed recruiters’ unreliable, invalid, and sometimes biased judgments. These findings mark the necessity and usefulness of novel, bias-free, and scientific approaches to candidate and employee screening and selection procedures in recruitment and human resources.
format	article
author	Mitchel Kappen Marnix Naber
author_facet	Mitchel Kappen Marnix Naber
author_sort	Mitchel Kappen
title	Objective and bias-free measures of candidate motivation during job applications
title_short	Objective and bias-free measures of candidate motivation during job applications
title_full	Objective and bias-free measures of candidate motivation during job applications
title_fullStr	Objective and bias-free measures of candidate motivation during job applications
title_full_unstemmed	Objective and bias-free measures of candidate motivation during job applications
title_sort	objective and bias-free measures of candidate motivation during job applications
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/7b3ae15bfbce4308b5db649d49b7a793
work_keys_str_mv	AT mitchelkappen objectiveandbiasfreemeasuresofcandidatemotivationduringjobapplications AT marnixnaber objectiveandbiasfreemeasuresofcandidatemotivationduringjobapplications
_version_	1718429236433256448

Objective and bias-free measures of candidate motivation during job applications

Ejemplares similares