Human–Algorithm Collaboration Works Best if Humans Lead (Because it is Fair!).
Autonomous algorithms are increasingly being used by organizations to reach ever increasing heights of organizational efficiency. The emerging business model of today therefore appears to be one where autonomous algorithms are gradually expanding their occupation into becoming a leading decision-mak...
| Publicado en: | Social Justice Research Vol. 35; no. 1; pp. 33 - 56 |
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| Autores principales: | , |
| Formato: | Artículo |
| Publicado: |
Springer Nature
Mar2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=155380575&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 155380575 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 08857466 4LL jtl: Social Justice Research issn: 08857466 maglogo: N pubinfo: dt: Mar2022 vid: 35 iid: 1 pid: 237 pub: Springer Nature artinfo: ui: 155380575 10.1007/s11211-021-00382-z ppf: 33 ppct: 23 formats: fmt: – @attributes: type: T – @attributes: type: P size: 1.2MB tig: atl: Human–Algorithm Collaboration Works Best if Humans Lead (Because it is Fair!). aug: au: De Cremer, David McGuire, Jack affil: Department of Management and Organisation, Centre on AI Technology for Humankind (AiTH), NUS Business School, National University of Singapore, 15 Kent Ridge Drive, 119245, Singapore, Singapore Cambridge University, Cambridge, UK su: Human beings Artificial intelligence Business models sug: subj: Human beings Artificial intelligence Business models keyword: Algorithm Collaboration Fairness Follower Human Leader Algorithm Collaboration Fairness Follower Human Leader ab: Autonomous algorithms are increasingly being used by organizations to reach ever increasing heights of organizational efficiency. The emerging business model of today therefore appears to be one where autonomous algorithms are gradually expanding their occupation into becoming a leading decision-maker, and humans by default become increasingly more subordinate to such decisions. We address the question of whether this business perspective is consistent with the sort of collaboration employees want to have with algorithms at work. We explored this question by investigating in what way humans preferred to collaborate with algorithms when making decisions. Using two experimental studies (Study 1, n = 237; Study 2, n = 684), we show that humans consider the collaboration with autonomous algorithms as unfair when the algorithm leads decision-making and will even incur high financial costs in order to avoid this. Our results also show that humans do not want to exclude algorithms entirely but seem to prefer a 60–40% human–algorithm partnership. These findings contrast the position taken by today's emerging business model on the issue of automated organizational decision-making. Our findings also provide support for the existence of an implicit theory—held by both present and future employees—that humans should lead and algorithms follow. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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