Unconscious bias. Is this affecting your recruitment process?
I am sure you must be looking for a solution to this challenge. Our nature makes us like people who are just like us. This process is unconscious. We do not do it intentionally.
To add diversity to your organization, removing unconscious bias is the priority.
We asked three experts from the HR Tech industry about their opinions on why unconscious bias should be removed from the recruitment process.
“Hiring should always be based on merit. We know that unconscious bias exists in every person, and this means that often, the right person does not get the job. The problem with some of the AI algorithms is that they use previous hires, which have been recruited through unconscious bias, as a learning mechanism. This leads to biased hires as happened at Amazon.
To remove the bias, you need to remove all biased data sets from the algorithms.
For example, you can determine what skills and experience are required in a job by using natural language processing and machine learning. The same technology can then be used to review a resume. Using matching technology, a non-biased match is achieved.”
“Hiring and recruiting is no place for discrimination or bias based on anything other than the ability to perform the job at hand while making a positive impact on the organization. Unfortunately, unconscious bias is just that. “Unconscious.” Here is one way you can eliminate bias in your HR technology software: Gender-neutral resume review – encourage your ATS administrators to turn-off candidate photo inclusion. Many times, there is a default to enable the software to associate the applicants’ email address with a social media footprint, and it can import their photo into the ATS.”
“Advanced Recruitment Platforms feature data-driven algorithms that can rank and match candidates to the jobs based on qualification, merit & skills. Yes! Skills! This eliminates the general bias faced by those talented individuals who miss out on opportunities due to their Ethnicity, Religion, Gender, Appearance, or other factors that cloud the judgment of a recruiter or interview panelist. Now that Machine Learning & AI in Recruitment Technology has moved out of its infancy; it has become imperative for organizations to adapt to these tech advancements and use them efficiently to hire diverse talent. Tech platforms like TalentRecruit are going to be the clear differentiators, especially for mandates where the organizations hire to establish an employer brand centered on equal opportunity.”
Imagine if technology shows its magic and gives you an unbiased hiring process!
A resume parser has the potential to hide biased data while parsing resumes. This data can be about age, gender, religious and political faith, marital status, candidate image, etc.
There is a lot more a parser can do to deal with this issue. Reach out to me to know more.
You might want to share your views on this topic. Please mention in comments.