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Crowdsourcing Algorithms Aim to Lift People From Poverty

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Crowdsourcing algorithms developed by a research team in the University of Illinois Coordinated Science Laboratory are helping lift people out of poverty.


A research team at the University of Illinois' Coordinated Science Laboratory (CSL) has developed crowdsourcing algorithms that are helping lift people out of poverty.

The researchers collaborated with Samasource on building algorithms that more efficiently match employees to jobs that complement their talents. The team builds algorithms that increase efficiency and reliability in many different types of systems, and their work could benefit Samasource, a nonprofit that connects people in countries such as India and Kenya to entry-level jobs.

Skillset sorting is difficult and time-consuming to do manually, but the algorithms have automated the process and mathematically guaranteed workers' skillsets are used in the optimal way. By perfectly utilizing worker capabilities, the team found the work is done more than six times faster.

"Not only does the algorithm improve efficiency, but it also operates in a decentralized way so that people can choose what job they want to do rather than being controlled centrally," notes CSL professor Lav Varshney.

From University of Illinois at Urbana-Champaign
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