Crushing It, dude? How Job Listings Turn Off Diverse Candidates

By Marissa Lang
San Francisco Chronicle

WWR Article Summary (tl;dr) In an effort to rout out coded language and divisive phrases, several companies have devised software that reads, detects and, in some cases, learns from job listings. The most recent entry comes from business software firm SAP, which this month released a new feature for SuccessFactors, its online human resources service: a job-listing analysis tool that mines text and uses machine learning to identify problematic phrases, suggest more innocuous alternatives and adapt to how candidates react.

San Francisco Chronicle

“Want to bro down and crush code?”

Hidden biases in job postings — like the infamous line above that tech startup Klout used in 2012 — as well as the words recruiters use to describe a position may be turning away potential employees long before they’ve had a chance to send in a resume.

As tech companies struggle with bringing more diverse candidates into the fold, that kind of slip-up is one diversity experts say they simply can’t afford.

In an effort to rout out coded language and divisive phrases, several companies have devised software that reads, detects and, in some cases, learns from job listings.

The most recent entry comes from business software firm SAP, which this month released a new feature for SuccessFactors, its online human resources service: a job-listing analysis tool that mines text and uses machine learning to identify problematic phrases, suggest more innocuous alternatives and adapt to how candidates react.

The software will become widely available in August.

“What we’ve seen is this classic approach in HR, which is looking in the rear-view mirror going, ‘Huh, your gender ratio is not right, you need to fix that.’ Or, ‘Your cultural diversity is lacking, you need to fix that.’ But isn’t that too late?” said Mike Ettling, president of SAP SuccessFactors. “You should be able to prevent the bias at the point where it gets originated. Actually when you write jobs specs, sometimes the bias is right there.”

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