By hiring more people from diverse backgrounds, a company becomes more multicultural, and benefits from well-trained and experienced additions. Indeed, employees with different experiences and educational backgrounds often bring greater productivity and a higher ROI to the company. And yet, many businesses struggle with diversity recruitment.
As technology becomes a bigger part of recruiting and hiring, it can help toward this purpose. In this piece, we'll speak to how HR departments can leverage technology to boost their efforts to hire more diverse workers.
Automated and Augmented Ad Writing
Algorithms, predictive analytics, and more have become more commonplace in HR and recruiting departments. Programs look at market data to make decisions to ensure that the right ad connects with the right candidates –– effectively creating augmented ads. These programs can also look at human-created ads to check for non-inclusive language and change it as needed in order to remove any unintentionally biased words and phrases.
It seems like not very long ago that "data analytics" was a buzz phrase attached to futuristic business ideas. Now, however, strategic use of data is considered essential. Today, in fact, many who pursue management and leadership roles in business, study data analytics as a primary concentration. This gives them the tools and understanding to help with the design and development of their own analytical processes according to need. With regard to diversity in hiring, this can mean the implementation of systems that help to assess candidate pools within set data parameters that intentionally ignore or exclude race, gender, and other elements that commonly play into bias.
Applicant Tracking Systems
Using an applicant tracking system enables you to collect candidate data and demographics in order to ensure compliance with regulations such as those imposed by the EEOC (which essentially make it illegal to discriminate in hiring). This way, your company can verify the diversity of the available candidate pool. Keep in mind, however, that candidates can decline to give relevant information, too –– meaning that sometimes the information from your pool can still be skewed.
Employing workforce analytics is a great way to check in with your current employees and pick up on certain trends –– such as pay gaps or differences in benefits and advancement opportunities between genders. This can help leaders make decisions about how they can help their current workforce and make the business environment more equitable. This will result in happier employees, and it will also boost the business's standing with potential candidates regardless of race, gender, background, etc. Meanwhile, the reverse is true also; many job seekers avoid applying to companies at which they are aware of a lack of diversity and equal conditions.
AI for Resume Screening
Businesses today also use AI to help recruiters during the daily job of having to look at hundreds of resumes that often look the same. Beyond making this process more efficient though, AI also reduces unconscious bias by actively ignoring gender, race, or age (or any other factors as directed by aforementioned experts in data analytics). Some AI programs can also remove certain things such as names or photos from resumes entirely –– resulting in "blind" resumes that show only qualifications and skills.
These processes aren't perfect. AI needs to be applied strategically in hiring, and even then, an NYU study found that AI itself suffers from a lack of diversity. That is to say, because this field of technology is not diverse, biases can creep into programs.
Provided you're aware of this however, you can take steps to use AI in a fair and unbiased manner. We hope that the tools and methods outlined above help your company with the objective of increasing diversity. The business will be better for it, both now and into the future.
Article written by Rebecca Jayme
Job.com is a digital recruitment innovator with a unique perspective: Delivering technology and capabilities that shake up the market by bringing together a data-driven approach based in AI and machine learning with high-level, human-capital-delivered solutions, designed to efficiently attract and retain the right talent and provide consumer-level user experiences throughout the hiring process.