Diversity JobsDiversity JobsIn 2024, more than 55% of hiring managers are using Artificial Intelligence (AI) to streamline the hiring process. These AI recruitment tools intend to help companies hire fresh talent, avoiding the typical bias that comes along with hiring. However, more job seekers are finding that these AI recruitment tools are replicating the same discriminatory practices as those who’ve created them.
Bias in AI recruitment tools have the potential to shut out an entire group of marginalized job seekers. While sourcing, screening, and interviewing job applicants, AI tools can operate with a narrow focus that undermines new talent being hired. What does this mean for job seekers? Well, it all starts with your resume and cover letter.
Gendered language bias is a known fact in society– the idea that some words appeal more to men, while others can easily be attributed to women. When it comes to AI recruitment tools sourcing new employees, the system is designed to look for and accept resumes/cover letters with masculine-appealing words like “leader”, “dominant”, or “efficient”.
Women tend to use softer sounding words like “support” or “aid” to describe their work experience. For female job seekers, this means that it’s more beneficial to include descriptor words that showcase both your hard and soft skills. Prove yourself to be a leader, if that’s who you are, and don’t shy away from hard-hitting words that depict you as someone who’s at the top of your field.
Social media plays a large part in how you appear to AI’s recruitment systems. Screening is the part of the hiring process that looks at who a job seeker is beyond what’s on their resume or cover letter. It’s so that the entire person is deemed suitable for the job. AI recruitment tools actively screen job seekers’ social media presence and respond to certain word choices. Job seekers who are active on social media can tailor their online presence to fit the job they want by including appropriate buzzwords in your profile or posts.
In a post-Covid work force, many recruitment processes have audio and video components. This new technology allows companies to hire talent that’s not only out of state, but sometimes, out of the country. However, AI isn’t advanced enough to understand many cultural and social differences, so it may deem certain candidates unfit based on its own lack of awareness.
For example, if a job seeker’s first language isn’t English, there may be a difference in their speech patterns. Similarly, neurodivergent job seekers may not be able to hold direct eye contact with a computer camera, which may signal to the AI tools that they aren’t a strong candidate. For these job seekers, this means that not every type of human being is being seen and valued as a potential job hire. And it’s a blind spot in the system’s learning.
Hiring bias is not a new phenomenon. Job seekers who belong to marginalized groups have long been overlooked for certain roles in the workforce. And when it comes to AI recruitment tools, the potential for hiring bias is far too great.
Employers should examine the inputs that feed their AI innovations. Setting diversity and inclusion as the basis of AI technology only improves the accuracy and efficiency of these tools. As employers work to mitigate these issues of bias, there’s a unique opportunity to hire fresh talent who otherwise would be passed over for their role.
