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dc.contributor.authorSchepman, Astrid
dc.contributor.authorRodway, Paul
dc.date.accessioned2020-06-03T08:12:51Z
dc.date.available2020-06-03T08:12:51Z
dc.identifierhttps://chesterrep.openrepository.com/bitstream/handle/10034/623459/SchepmanRodway_ArtificialIntelligence_AAM.pdf?sequence=4
dc.identifier.citationSchepman, A. & Rodway, P. (2020). Initial validation of the general attitudes towards Artificial Intelligence Scale. Computers in Human Behavior Reports, 1, 100014. https://doi.org/10.1016/j.chbr.2020.100014en_US
dc.identifier.urihttp://hdl.handle.net/10034/623459
dc.descriptionAuthor Accepted Manuscript with Appendix A (Sources of News Stories) and Appendix B (General Attitudes Towards Artificial Intelligence Scale, with instructions and scoring). For data files, please follow the DOI https://doi.org/10.1016/j.chbr.2020.100014 to the publisher's site. This article is available Open Access via the Publisher's site: https://www.sciencedirect.com/science/article/pii/S2451958820300142en_US
dc.description.abstractA 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.en_US
dc.publisherElsevieren_US
dc.relation.urlhttps://www.sciencedirect.com/science/article/pii/S2451958820300142en_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.subjectArtificial Intelligenceen_US
dc.subjectPsychometricsen_US
dc.subjectSurveyen_US
dc.subjectIndexen_US
dc.subjectAttitudesen_US
dc.subjectPerceptionen_US
dc.subjectQuestionnaireen_US
dc.titleInitial validation of the general attitudes towards Artificial Intelligence Scaleen_US
dc.typeArticleen_US
dc.contributor.departmentUniversity of Chesteren_US
dc.identifier.journalComputers in Human Behavior Reportsen_US
or.grant.openaccessYesen_US
rioxxterms.funderUnfundeden_US
rioxxterms.identifier.projectUnfundeden_US
rioxxterms.versionAMen_US
rioxxterms.versionofrecordhttps://doi.org/10.1016/j.chbr.2020.100014en_US
rioxxterms.licenseref.startdate2020-05-18
refterms.dateFCD2020-06-02T14:36:43Z
refterms.versionFCDAM
refterms.dateFOA2020-05-18T00:00:00Z
rioxxterms.publicationdate2020-05-18
dc.dateAccepted2020-04-28
dc.date.deposited2020-06-03en_US
dc.indentifier.issn2451-9588en_US


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