Ar­ti­fi­cial in­tel­li­gence may weigh in on your em­ploy­ment application

Grow­ing num­ber of em­ploy­ers are us­ing data-driven tools to pre-screen job ap­pli­cants

StarMetro Vancouver - - COVER STORY - ALEX MCKEEN

Thurs­day, June 7, 2018

In 2018, ro­bots do not hire peo­ple. But ar­ti­fi­cial in­tel­li­gence may con­tinue to play an in­creas­ingly sig­nif­i­cant role in deter­min­ing which can­di­dates get in­vited to in­ter­views in the fu­ture world of work, as Van­cou­ver em­ploy­ers adapt to us­ing datadriven tools to pre-screen po­ten­tial em­ploy­ees.

Some level of au­to­mated screen­ing has been a com­mon hu­man resource prac­tice for years — es­pe­cially among large com­pa­nies that may be field­ing hun­dreds of ap­pli­ca­tions at once. Em­ploy­ers may, for in­stance, per­form key­word searches on batches of re­sumés to de­ter­mine which can­di­dates have some of the char­ac­ter­is­tics they’re look­ing for.

But as au­to­ma­tion be­comes more sophisticated, so too does the po­ten­tial for ap­pli­cant screen­ing. And that’s changing the way com­pa­nies think about hir­ing.

Van­cou­ver com­pany Bean­works, which pro­vides teams of ac­coun­tants with an ac­counts payable au­to­ma­tion tool, uses Plum, a data-driven Cana­dian tool that pre­dicts how well can­di­dates will do a job.

Plum, which is based out of the tech­nol­ogy hub of Kitch­ener-water­loo in On­tario, has the tag line “pre­dict cer­tain.”

“So plum is a great data point but it’s not the en­tire data set,” said Karim Ben-jaa­far, pres­i­dent of Bean­works. “We look at ev­ery sin­gle re­sumé and we don’t let plum make the de­ci­sion for us.”

Plum works by col­lect­ing data on peo­ple who have suc­ceeded in roles through an on­line as­sess­ment sys­tem, and mea­sur­ing ap­pli­cants rel­a­tive to one an­other on the broad traits de­ter­mined to be shared by the success sto­ries.

Use of au­to­mated tools is not with­out its de­trac­tors. Some worry the use of ar­ti­fi­cial in­tel­li­gence to aid with hir­ing could be fraught with bias, since data based on peo­ple who have al­ready suc­ceeded in the job may not in­clude those who would have suc­ceeded at the job, but haven’t had the op­por­tu­nity due to un­con­scious bias.

Read the full story on thes­tar.com/van­cou­ver

COURTESY OF BEAN­WORKS

Van­cou­ver com­pa­nies like Bean­works are in­creas­ingly us­ing data-driven tools to help pre-screen job ap­pli­cants.

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