Combatting Unconscious Hiring Bias
While lawyers are, undeniably, in the “word business,” we are also human and may not be aware of how powerful words are in influencing our hiring decisions.
Kieran Snyder, cofounder of Textio, an advanced machine learning platform comparing a job post’s wording to more than 40 million other listings to predict how well it will perform before it’s published. “With the right data, our technology can predict how your job post will be received before you put it out for thousands of job applicants to read,” Snyder says. Not only does Textio help companies comply with increasing federal, state, and local regulations demanding gender equity in job listings, but in focusing on the language used, Textio is a critical tool in combating unconscious bias in the workplace.
Snyder shares her key insights to understand how language impacts the hiring process, and how all of us can work to overcome unconscious bias.
- Gender-neutral listings get faster results: “The use of gender-specific language predicts the gender of the person you hire at the end,” Snyder says. “A highly masculine listing makes it twice as likely that the position will be filled by a man. Similarly, a highly feminine listing makes it twice as likely that the position will be filled by a woman.” A gender-neutral listing simply performs much better than one with a strong masculine or feminine tone. “This gender neutrality is not just valuable for diversity reasons. The listings that use gender neutral language are filled two weeks faster than job listings that have either a strong masculine or feminine tone,” she says. “On average, we are saving our customers 14 days per listing. And that is a significant saving.”
- Using words for maximum reach: Textio analyzes millions of listings to see which words and phrases attract more applicants of a specific gender, or more diverse applicants. Snyder explains that if an employer creates job listings that systematically select out populations in recruiting, these listings are more likely to underperform. “If you miss the opportunity to reach to half of the population, of course it will take longer to fill a position,” she says.
- ROI: Textio scores each listing on a one-hundred-point scale. “If a user gets above the score of ninety that is where a lot of interesting return on investment is observed,” says Snyder. “Hiring teams who maintain a Textio Score of 90 or higher attract an applicant pool that is on average 24% more qualified and 12% more diverse — and they do it 17% faster than their competition.” She adds, “Surely these statistics are connected. Of course, you fill a position quicker when you reach diverse pool of candidates.”
- Comprehensive data analytics: Comprehensive data and analysis give companies an objective, judgement-free look at how well they’re performing. “Textio has observed that its customers start keeping track of bias in different parts of their organizations,” explains Snyder. “They also use that data to change their practices and train employees.” Many clients also create a score threshold before allowing the publication of a listing. Textio’s platform rates job listings on neutrality (lack of bias) and overall effectiveness. Snyder says that it is not unusual for companies to allow only job listings that score sufficiently high. “We can see that this data also creates a quantified compliance record,” she adds.
- Language evolution: “We help our users get better, not be replaced with a machine,” Snyder says. Textio aims to help companies write better job listings that fit their unique company cultures and styles, not automatically generate cookie-cutter listings. “The platform works to optimize users’ style and help them to reduce their unconscious bias. Textio does not help you if you are purposefully biased!” Snyder also explains that Textio keeps track of speech changes because language and its patterns change all the time. Textio learns from its strongest writers and helps others to adopt the best practices at the time. “Some people are good writers and they innovate. They find better, more effective, and more efficient ways to communicate all the time,” Snyder explains. “That is how a language evolves. And we help others to tap into this collective knowledge.”
- Tracking trends: Textio also finds other interesting trends. For example, Textio can track how words and phrases go in and out of fashion. According to Snyder “big data” was a positive phrase a few years ago; over time it became a neutral, filler phrase in job listings. It is now a negative phrase that turns off certain qualified candidates. “Artificial intelligence” is another phrase that has recently undergone a similar evolution. These linguistic preferences can also be location specific. For example, “cool” jobs are filled much quicker in London than in Sydney and New York.
In addition to helping lawyers eliminate unconscious bias from the hiring process, from a legal operations perspective, a tool like Textio is an easy sell from an ROI and business impact perspective. How are you combatting unconscious hiring bias in your organization? We’d love to hear your thoughts and ideas on this important topic — email or tweet us!
This article was originally published by Above the Law.