DESCANT Project - Detecting Stereotypes in Human Computational Tasks

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DESCANT Project - Detecting Stereotypes in Human Computational Tasks

The DESCANT project is funded by the Research and Innovation Foundation (RIF) of the Republic of Cyprus under grant agreement EXCELLENCE/0918/0086 and is hosted by the CYENS Centre of Excellence

DESCANT shall contribute to the smart growth of R&D in Cyprus, as its objectives are in line with the Smart Specialization Strategy, which designates ICT as a horizontal priority, as well as Cyprus’ Digital Strategy Goals and specifically, Digital Entrepreneurship.  

Crowdsourcing has enabled the development of novel “hybrid human-machine information systems,” which benefit from including humans in the loop when facing computational tasks that are still better solved by humans than machines. However, hybrid systems are only as good as the data with which they are built and ensuring the quality of workers’ contributions is often non-trivial. DESCANT addresses a particular concern for crowdsourced data quality: the expression of social stereotypes in the data collected.  


Curated by:
DESCANT_CY
Curation policy:
Not specified
Created:
March 9, 2021
Harvesting API:
OAI-PMH Interface

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