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Theoretical Underpinnings and Practical Challenges of Crowdsourcing as a Mechanism for Academic Study

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Title:Theoretical Underpinnings and Practical Challenges of Crowdsourcing as a Mechanism for Academic Study
Authors:Correia, António
Jameel, Shoaib
Schneider, Daniel
Fonseca, Benjamim
Paredes, Hugo
Keywords:2020 Vision of Crowd Science
crowd science
crowdsourcing
human-machine hybrid computation
massively collaborative science
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Date Issued:07 Jan 2020
Abstract:Researchers in a variety of fields are increasingly adopting crowdsourcing as a reliable instrument for performing tasks that are either complex for humans and computer algorithms. As a result, new forms of collective intelligence have emerged from the study of massive crowd-machine interactions in scientific work settings as a field for which there is no known theory or model able to explain how it really works. Such type of crowd work uses an open participation model that keeps the scientific activity (including datasets, methods, guidelines, and analysis results) widely available and mostly independent from institutions, which distinguishes crowd science from other crowd-assisted types of participation. In this paper, we build on the practical challenges of crowd-AI supported research and propose a conceptual framework for addressing the socio-technical aspects of crowd science from a CSCW viewpoint. Our study reinforces a manifested lack of systematic and empirical research of the symbiotic relation of AI with human computation and crowd computing in scientific endeavors.
Pages/Duration:10 pages
URI:http://hdl.handle.net/10125/64310
ISBN:978-0-9981331-3-3
DOI:10.24251/HICSS.2020.568
Rights:Attribution-NonCommercial-NoDerivatives 4.0 International
https://creativecommons.org/licenses/by-nc-nd/4.0/
Appears in Collections: 2020 Vision of Crowd Science


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