Can Technology Improve Diversity in Hiring?

Oleeo’s Jeanette Maister on blind screening, gender-neutral job ads, AI bias

Roy Maurer By Roy Maurer October 5, 2018
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​Jeanette Maister is the managing director, head of the Americas at Oleeo.

​There's still much work to do to eliminate bias in hiring, but one thing's for sure—technology will play a key role in getting there, says Jeanette Maister, a global talent acquisition leader with extensive experience in recruiting technology and hiring for diversity.

Maister is the managing director, head of the Americas at Oleeo, a talent acquisition technology company based in London. She's spent years in recruiting-leadership roles at Credit Suisse, Lehman Brothers and Gartner.

Maister spoke with SHRM Online about efforts to phase out hiring bias, including conducting blind resume screening and writing gender-neutral job postings.

[SHRM members-only online discussion platform: SHRM Connect]

SHRM Online: For years, we've been aware of the benefits of hiring for diversity—have recruiting efforts thus far met expectations?

Maister: People want to do better. A lot of organizations want to do the right thing, but at times efforts can be haphazard and not baked into the process. Diversity recruiting should not just be a program. Even though companies are saying they are focusing on diversity, they are only using some bells and whistles while still doubling down on the same approaches they have used since the 1960s. Rather than reduce bias and foster an inclusive work culture, the goal of these outdated approaches is to pre-empt lawsuits.

In U.S. commercial banks, even with the use of diversity programs, equality is not improving. Within the last few years, women's representation in management in that sector has dropped. Even in Silicon Valley, where many leaders tout the need to increase diversity for both business and social justice reasons, most tech jobs are still held by white men.

It is disappointing. Employers need to be much more proactive. At the bottom of every job description you see, "We're an equal opportunity employer." Companies look backward, asking if the candidates who interviewed were diverse enough and if they matched the overall applicant pool for diversity. It's reactive. It's after the fact. Technology can make prescriptive recommendations based on hundreds of data points to match the best candidates for the role based on job fit, while ensuring the company isn't making an adverse selection. That will help. It's a piece of the puzzle, to ensure more diverse applicants receive interviews, at a minimum.

SHRM Online: What are your thoughts about the blind-screening trend?

Maister: It's interesting that it's considered a trend in the U.S. It's more established in the U.K. and across Europe. When I ask audiences in the U.S. if they're doing blind screening or anonymizing names on resumes, very few people raise their hands. When I ask how many are thinking about doing it, a lot more hands go up. If you ask the same questions in the U.K., most people are already doing it.

I think it's important. So many studies have been done that show applicants with white-sounding names are more likely to get selected for interviews than those with black-sounding names. It's important to take out any of these unintentional biases. Many organizations have implemented processes of removing names, nationalities and university names from resumes when given to hiring managers so they can solely judge on merit and experience.

SHRM Online: What about the issue of gender-based language in job postings?

Maister: That's a problem. From the very beginning of the candidate hunt, the way you write your job descriptions could already be limiting which gender will be the majority of your applicants. A study by the Journal of Personality and Social Psychology found the gendered wording in job descriptions affected who would apply for those positions. They found women were more interested in male-dominated positions when the advertisements were unbiased and did not refer to the applicant as "he." Employers absolutely need to ensure that language doesn't dissuade women from applying for roles. But it's not just the language; it's the job post itself. Research shows that women will only apply to the job if they meet 100 percent of the criteria, while men will usually apply if they meet just 60 percent of listed requirements.

A lot of great companies out there have tools where you can upload your job description, and it flags how likely it is to turn off women or recommends more gender-neutral words that will attract people regardless of whether they're male or female.

SHRM Online: Do you also support employers trimming job requirements to broaden the applicant pool?

Maister: Absolutely. And picking the pieces that are truly important to the job. These job descriptions are like a laundry list. And no one like that typically exists anyway. Cut it down. Identify which requirements are nice to have versus must-have, and remove the nice-to-have requirements from the ad. Using algorithms and intelligent automation, we can finally level the playing field with the program's ability to pick out top candidates. Doing so can and will get you the best candidate in the right position.

SHRM Online: What about the argument that coders' biases can be incorporated into artificial intelligence (AI) technology that is meant to help prevent bias?

Maister: That is an issue. It's one of the reasons that we added the Equal Employment Opportunity Commission (EEOC) selection compliance rates to our algorithm, because we want to be compliant. Technology can be unintentionally biased, so we figured that adding the EEOC rates would prevent that.

We're just at the beginning of this AI journey. Every organization has to get more sophisticated and think about this. You can have great automation [and] AI, but you have to look out for these pitfalls. Watch out, and make sure you ask any vendor you use about the data science behind their tools. You can imagine a time in the near future when this area will be more heavily regulated.

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