Publication | Closed Access
Crowdsourcing, Mixed Elastic Systems and Human-Enhanced Computing–A Survey
21
Citations
48
References
2017
Year
Artificial IntelligenceEngineeringHuman InterventionIntelligent SystemsComputational Social ScienceData ScienceHumanartificial Intelligence CollaborationHuman ComputationMixed Elastic SystemsKnowledge DiscoveryComputer ScienceCrowdsourcingHuman Systems IntegrationCrowd ComputingHybrid IntelligenceSocial ComputingHuman-ai InteractionHuman-computer InteractionBig Data
State-of-the-art practices have recognized the utility of leveraging human intervention as a crucial aspect of modern computing systems. The emerging crowdsourcing paradigm is based on harnessing human intelligence, effort and rational behaviors to augment computation and analysis. In addition to the crowdsourcing paradigm, new techniques have emerged that incorporate machine and human computational resources together forming a hybrid intelligence when addressing complex problems and tasks. This combined technique is particularly impactful if human and machine contributions can scale automatically in response to their respective efficiency and effectiveness when addressing subsets of a bigger problem - an approach that we have named mixed elastic systems. In this survey, we highlight state-of-the-art projects that investigate crowdsourcing, hybrid intelligence systems and mixed elastic systems. We also present a taxonomy and classification of the broader domain of human-enhanced computing systems as it assimilates crowdsourcing, hybrid intelligence, and mixed elastic systems.
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