Initial validation of the general attitudes towards Artificial Intelligence Scale

A new General Attitudes towards Artificial Intelligence Scale (GAAIS) was developed. The scale underwent initial statistical validation via Exploratory Factor Analysis, which identified positive and negative subscales. Both subscales captured emotions in line with their valence. In addition, the pos...

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Autores principales:	Astrid Schepman, Paul Rodway
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2020
Materias:	Artificial intelligence Psychometrics Questionnaire Index Attitudes Perception Electronic computers. Computer science QA75.5-76.95 Psychology BF1-990
Acceso en línea:	https://doaj.org/article/1133d2a61e8b4505bd74f4ec4dd8dbad
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spelling	oai:doaj.org-article:1133d2a61e8b4505bd74f4ec4dd8dbad2021-12-01T05:03:11ZInitial validation of the general attitudes towards Artificial Intelligence Scale2451-958810.1016/j.chbr.2020.100014https://doaj.org/article/1133d2a61e8b4505bd74f4ec4dd8dbad2020-01-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2451958820300142https://doaj.org/toc/2451-9588A new General Attitudes towards Artificial Intelligence Scale (GAAIS) was developed. The scale underwent initial statistical validation via Exploratory Factor Analysis, which identified positive and negative subscales. Both subscales captured emotions in line with their valence. In addition, the positive subscale reflected societal and personal utility, whereas the negative subscale reflected concerns. The scale showed good psychometric indices and convergent and discriminant validity against existing measures. To cross-validate general attitudes with attitudes towards specific instances of AI applications, summaries of tasks accomplished by specific applications of Artificial Intelligence were sourced from newspaper articles. These were rated for comfortableness and perceived capability. Comfortableness with specific applications was a strong predictor of general attitudes as measured by the GAAIS, but perceived capability was a weaker predictor. Participants viewed AI applications involving big data (e.g. astronomy, law, pharmacology) positively, but viewed applications for tasks involving human judgement, (e.g. medical treatment, psychological counselling) negatively. Applications with a strong ethical dimension led to stronger discomfort than their rated capabilities would predict. The survey data suggested that people held mixed views of AI. The initially validated two-factor GAAIS to measure General Attitudes towards Artificial Intelligence is included in the Appendix.Astrid SchepmanPaul RodwayElsevierarticleArtificial intelligencePsychometricsQuestionnaireIndexAttitudesPerceptionElectronic computers. Computer scienceQA75.5-76.95PsychologyBF1-990ENComputers in Human Behavior Reports, Vol 1, Iss , Pp 100014- (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Artificial intelligence Psychometrics Questionnaire Index Attitudes Perception Electronic computers. Computer science QA75.5-76.95 Psychology BF1-990
spellingShingle	Artificial intelligence Psychometrics Questionnaire Index Attitudes Perception Electronic computers. Computer science QA75.5-76.95 Psychology BF1-990 Astrid Schepman Paul Rodway Initial validation of the general attitudes towards Artificial Intelligence Scale
description	A new General Attitudes towards Artificial Intelligence Scale (GAAIS) was developed. The scale underwent initial statistical validation via Exploratory Factor Analysis, which identified positive and negative subscales. Both subscales captured emotions in line with their valence. In addition, the positive subscale reflected societal and personal utility, whereas the negative subscale reflected concerns. The scale showed good psychometric indices and convergent and discriminant validity against existing measures. To cross-validate general attitudes with attitudes towards specific instances of AI applications, summaries of tasks accomplished by specific applications of Artificial Intelligence were sourced from newspaper articles. These were rated for comfortableness and perceived capability. Comfortableness with specific applications was a strong predictor of general attitudes as measured by the GAAIS, but perceived capability was a weaker predictor. Participants viewed AI applications involving big data (e.g. astronomy, law, pharmacology) positively, but viewed applications for tasks involving human judgement, (e.g. medical treatment, psychological counselling) negatively. Applications with a strong ethical dimension led to stronger discomfort than their rated capabilities would predict. The survey data suggested that people held mixed views of AI. The initially validated two-factor GAAIS to measure General Attitudes towards Artificial Intelligence is included in the Appendix.
format	article
author	Astrid Schepman Paul Rodway
author_facet	Astrid Schepman Paul Rodway
author_sort	Astrid Schepman
title	Initial validation of the general attitudes towards Artificial Intelligence Scale
title_short	Initial validation of the general attitudes towards Artificial Intelligence Scale
title_full	Initial validation of the general attitudes towards Artificial Intelligence Scale
title_fullStr	Initial validation of the general attitudes towards Artificial Intelligence Scale
title_full_unstemmed	Initial validation of the general attitudes towards Artificial Intelligence Scale
title_sort	initial validation of the general attitudes towards artificial intelligence scale
publisher	Elsevier
publishDate	2020
url	https://doaj.org/article/1133d2a61e8b4505bd74f4ec4dd8dbad
work_keys_str_mv	AT astridschepman initialvalidationofthegeneralattitudestowardsartificialintelligencescale AT paulrodway initialvalidationofthegeneralattitudestowardsartificialintelligencescale
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Initial validation of the general attitudes towards Artificial Intelligence Scale

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