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dc.contributor.authorThompson, Terrie-Lynnen_UK
dc.contributor.authorGraham, Bruceen_UK
dc.contributor.editorDe Laat, Maartenen_UK
dc.contributor.editorRyberg, Thomasen_UK
dc.contributor.editorBonderup Dohn, Ninaen_UK
dc.contributor.editorHansen, Stig Børsenen_UK
dc.contributor.editorHansen, Jens Jørgenen_UK
dc.description.abstractArtificial intelligence (AI) is increasingly manifest in everyday work, learning, and living. Reports attempting to gauge public perception suggest that amidst exaggerated expectations and fears about AI, citizens are sceptical and lack understanding of what AI is and does (Archer et al., 2018). Professional workers practice at the intersection of such public perceptions, the AI industry, and regulatory frameworks. Yet, there is limited understanding of the day-to-day interactions and predicaments between workers, AI systems, and the publics they serve. This includes how these interactions and predicaments generate opportunities for learning and highlight new digital fluencies needed. We bring social and computing science perspectives to begin to examine the prevailing AI narratives in professional work and learning practices. Some AIs (such as deep machine learning systems) are so sophisticated that a human-understandable explanation of how it works may not be possible. This raises questions about what professional practitioners are able to know about the AI systems they use: their new digital co-workers. We argue that a co-constitutive human-AI perspective could provide useful insights on questions such as: (1) How is professional expertise and judgment re-distributed as workers negotiate and learn with AI systems? (2) What trust and confidence in new AI-infused work practices is needed or possible and how is this mediated? (3) What are the implications for professional learning: both learning within work and the workplace and more formal curriculum? Given the early stages of this field of inquiry, our aim is to evoke discussion of alternative human-AI narratives suited for the messy—and often unseen—realities of everyday practices.en_UK
dc.publisherAalborg Universityen_UK
dc.relationThompson T & Graham B (2020) More-than-human approach to researching AI at work: Alternative narratives for AI and networked learning. In: De Laat M, Ryberg T, Bonderup Dohn N, Hansen SB & Hansen JJ (eds.) NETWORKED LEARNING 2020: Proceedings for the 12th International Conference on Networked Learning. Networked Learning Conference Proceedings, 12. Twelfth International Conference on Networked Learning 2020, Online, 18.05.2020-20.05.2020. Kolding, Denmark: Aalborg University, pp. 293-300.en_UK
dc.relation.ispartofseriesNetworked Learning Conference Proceedings, 12en_UK
dc.rightsThe publisher has not responded to our queries therefore this work cannot be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.en_UK
dc.titleMore-than-human approach to researching AI at work: Alternative narratives for AI and networked learningen_UK
dc.typeConference Paperen_UK
dc.rights.embargoreason[thompson graham_2020_nl conf paper.pdf] The publisher has not responded to our queries. This work cannot be made publicly available in this Repository therefore there is an embargo on the full text of the work.en_UK
dc.type.statusAM - Accepted Manuscripten_UK
dc.citation.btitleNETWORKED LEARNING 2020: Proceedings for the 12th International Conference on Networked Learningen_UK
dc.citation.conferencedates2020-05-18 - 2020-05-20en_UK
dc.citation.conferencenameTwelfth International Conference on Networked Learning 2020en_UK
dc.publisher.addressKolding, Denmarken_UK
dc.contributor.affiliationComputing Scienceen_UK
rioxxterms.apcnot requireden_UK
rioxxterms.typeConference Paper/Proceeding/Abstracten_UK
local.rioxx.authorThompson, Terrie-Lynn|0000-0002-8166-3791en_UK
local.rioxx.authorGraham, Bruce|0000-0002-3243-2532en_UK
local.rioxx.projectInternal Project|University of Stirling|
local.rioxx.contributorDe Laat, Maarten|en_UK
local.rioxx.contributorRyberg, Thomas|en_UK
local.rioxx.contributorBonderup Dohn, Nina|en_UK
local.rioxx.contributorHansen, Stig Børsen|en_UK
local.rioxx.contributorHansen, Jens Jørgen|en_UK
local.rioxx.filenamethompson graham_2020_nl conf paper.pdfen_UK
Appears in Collections:Faculty of Social Sciences Conference Papers and Proceedings

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