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Artificial Intelligence, Employee Engagement, Fairness, and Job Outcomes

dc.contributor.authorHughes, Claretha
dc.contributor.authorRobert, Lionel + "Jr"
dc.contributor.authorFrady, Kristin
dc.contributor.authorArroyos, Adam
dc.date.accessioned2019-08-05T12:28:53Z
dc.date.available2019-08-05T12:28:53Z
dc.date.issued2019-07-23
dc.identifier.citationHughes, C., Robert, L., Frady, K., Arroyos, A., (2019), "Artificial Intelligence, Employee Engagement, Fairness, and Job Outcomes", Managing Technology and Middle- and Low-skilled Employees (The Changing Context of Managing People), Emerald Publishing Limited, pp. 61-68. https://doi.org/10.1108/978-1-78973- 077-720191005en_US
dc.identifier.issn978-1-78973-078-4
dc.identifier.urihttps://hdl.handle.net/2027.42/150204
dc.description.abstractChapter 5, “Artificial Intelligence, Employee Engagement, Fairness and Job Outcomes,” defines AI as the ability of a computer system to sense, reason, and respond to the environment. Computer systems with advanced AI can engage in sensing, reasoning, and responding in the most complex and dynamic environments. AI systems are being adapted rapidly by organizations to help manage their workforce. The reason for the popularity of AI is twofold. One, organizations now have access to huge amounts of data (i.e., big data) about their business operations which can be leveraged to make more efficient and effective management decisions. Two, advances in AI now afford organizations the ability to capture and process this data in real time. Organizations can now incorporate the latest information into their decision making even in the most complex and dynamic competitive markets. Despite this, management through AI also presents new challenges to employees who are now both directed and held accountable by AI.en_US
dc.description.sponsorshipNational Science Foundation CHS-1617820en_US
dc.language.isoen_USen_US
dc.publisherEmerald Publishing Limiteden_US
dc.subjectArtificial Intelligenceen_US
dc.subjectArtificial Intelligence Fairnessen_US
dc.subjectArtificial Intelligence Controlsen_US
dc.subjectArtificial Intelligence Managementen_US
dc.subjectArtificial Intelligence Employee Engagementen_US
dc.subjectalgorithm managementen_US
dc.subjectAI Managementen_US
dc.subjectArtificial Intelligence Employee Controlsen_US
dc.subjectArtificial Intelligence Outcome Controlen_US
dc.subjectArtificial Intelligence Trusten_US
dc.subjectArtificial Intelligence Perceived Risken_US
dc.subjectArtificial Intelligence Procedural Fairnessen_US
dc.subjectArtificial Intelligence Distributive Fairnessen_US
dc.subjectArtificial Intelligence Interactional Fairnessen_US
dc.subjectArtificial Intelligence Technology Characteristicsen_US
dc.subjectArtificial Intelligence Perceived Ease of Useen_US
dc.subjectArtificial Intelligence Perceived Usefulnessen_US
dc.subjectArtificial Intelligence and Job Satisfactionen_US
dc.subjectArtificial Intelligence and Job Meaningfulnessen_US
dc.subjectArtificial Intelligence and Retentionen_US
dc.subjectAI-driven systemsen_US
dc.subjectArtificial Intelligence Employee Motivationen_US
dc.subjectArtificial Intelligence and Organizational Justiceen_US
dc.subjectArtificial Intelligence and Goalsen_US
dc.subjectalgorithmic managementen_US
dc.subjectalgorithmic controlsen_US
dc.titleArtificial Intelligence, Employee Engagement, Fairness, and Job Outcomesen_US
dc.title.alternativeChapter 5 Artificial Intelligence, Employee Engagement, Fairness, and Job Outcomesen_US
dc.typeBook Chapteren_US
dc.subject.hlbsecondlevelInformation and Library Science
dc.subject.hlbtoplevelSocial Sciences
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumInformation, School ofen_US
dc.contributor.affiliationumRoboticsen_US
dc.contributor.affiliationotherUniversity of Arkansasen_US
dc.contributor.affiliationotherClemson Universityen_US
dc.contributor.affiliationumcampusAnn Arboren_US
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/150204/1/AI, Employee Engagement, Fairness, and Job Outcomes (Preprint).pdf
dc.identifier.doi10.1108/978-1-78973-077-720191005
dc.identifier.sourceManaging Technology and Middle- and Low-skilled Employeesen_US
dc.identifier.orcid0000-0002-1410-2601en_US
dc.identifier.name-orcidRobert, Lionel P.; 0000-0002-1410-2601en_US
dc.owningcollnameInformation, School of (SI)


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