Is Quality Control Pointless?

dc.contributor.authorKrause, Markus
dc.contributor.authorAfzali, Farhad Mohammad
dc.contributor.authorCaton, Simon
dc.contributor.authorHall, Margeret
dc.date.accessioned2019-01-03T00:36:24Z
dc.date.available2019-01-03T00:36:24Z
dc.date.issued2019-01-08
dc.description.abstractIntrinsic to the transition towards, and necessary for the success of digital platforms as a service (at scale) is the notion of human computation. Going beyond ‘the wisdom of the crowd’, human computation is the engine that powers platforms and services that are now ubiquitous like Duolingo and Wikipedia. In spite of increasing research and population interest, several issues remain open and in debate on large-scale human computation projects. Quality control is first among these discussions. We conducted an experiment with three different tasks of varying complexity and five different methods to distinguish and protect against constantly underperforming contributors. We illustrate that minimal quality control is enough to repel constantly underperforming contributors and that this is constant across tasks of varying complexity.
dc.format.extent10 pages
dc.identifier.doihttps://doi.org/10.24251/HICSS.2019.636
dc.identifier.isbn978-0-9981331-2-6
dc.identifier.urihttp://hdl.handle.net/10125/59964
dc.language.isoeng
dc.relation.ispartofProceedings of the 52nd Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectCrowd Science
dc.subjectKnowledge Innovation and Entrepreneurial Systems
dc.subjectCrowd labour, Crowdwork, Quality control, human computation, NLP
dc.titleIs Quality Control Pointless?
dc.typeConference Paper
dc.type.dcmiText

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