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Can Artificial Intelligence Help Increase Diversity in IT?

 
Applied properly, AI might help bridge the diversity gap in IT First, we have to deal with the elephant in the room. Amazon had a well-publicized failure when they tried to use AI for this very purpose. Their recruiting tool developed a learned gender bias, boosting male applicants over females. A model is only as good as its data. If you fed it thousands of resumes where 70% are male, what conclusions do you think it would draw concerning the equality of the sexes?

Image: Jakub Krechowicz - stock.adobe.comImage: Jakub Krechowicz - stock.adobe.com

There are three key areas of focus when looking at how artificial intelligence can help remove bias from our hiring process. These are creating job postings, evaluating resumes, and interviewing candidates. 

You may not realize it, but your perfectly crafted job ad is unknowingly discouraging qualified candidates from applying. In a ZipRecruiter study, 70% of job postings contained masculine words. This finding was pervasive across all industries. When wording was changed to be more gender neutral (using words like support and understand versus aggressive or leader), hiring managers saw a 42% increase in responses. So how does AI spot these imbalances? By allowing the algorithm to churn over millions of job ads and their corresponding resumes, it can discern patterns hiding in the data. By simply using inclusive writing in our postings, we won’t turn away qualified applicants at the door and will maximize the diversity of our selection pool. 

We may have a resume pool brimming with diversity, but we’ve exacerbated our next problem — evaluating resumes. A single job posting may attract 100 resumes. With the recent explosion of remote work, the response rate can get multiplied even further. It’s not possible for humans to fairly evaluate hundreds of candidates. We unknowingly lean on our biases to weed out candidates that don’t fit the preset model in our head. Did they go to the right college? Where did they work last? Were they referred Interviews should be highly structured where each candidate is presented with the same batch of questions. This rarely happens in an actual interview. Real-life interactions tend to be more fluid, less disciplined and highly subjective. It’s impossible to isolate all the outside variables because no two interviews will be the same. Using AI, digital interviews remove these limitations AI is already ubiquitous in the HR industry. Sixty seven percent of hiring managers and recruiters reported that artificial intelligence was a significant time saver, according to a LinkedIn survey. Handing that much power over to a computer makes many uneasy, but we have to realize that AI is designed Artificial intelligence isn’t perfect and can fall prey to current hiring pitfalls if we aren’t careful. With proper auditing and governance, AI can help us bridge the gap to a more diverse workforce.

Mark Runyon works as a principal consultant for Improving in Atlanta, Georgia. He specializes in the architecture and development of enterprise applications, leveraging cloud technologies. He is a frequent speaker and contributing writer for the Enterprisers Project.

 

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