This is a guest post and infographic provided This Way Global.
Using artificial intelligence in recruiting software has the potential to streamline the hiring process. It also has the ability to identify top applicants without relying on the biases that a human recruiter could unconsciously hold. This means recruiting AI can make the hiring process overall easier and more equal. With this visual deep dive’s support, let’s look at how AI improves hiring diverse employees.Â
There have been some problems with recruiting AI in the past. Because the AI is programmed with data generated from human recruiters, our preferences and biases are often integrated into the software. This occurs especially through the use of keywords. Certain keywords are based on human recruiters’ search terms, reflecting the unfair preferences we unconsciously have.Â
For recruiting AI to be successful, it must be programmed with a large amount of varied data. Using a recruiter’s narrower search terms shifts value from a candidate’s qualifications to just their ability to include the right keywords in their application. Problems also arise from the use of too few keywords because of how subjective language can be. Colloquial terms used by subsets of English speakers end up harming a candidate and perpetuating the company’s lack of diversity.Â
Use these practices to program an unbiased recruiting AI:
- Collect data from a wide variety of places (industries, jobs, and candidates)
- Remove factors like age, gender, and names that spark implicit bias
- Value more factors like interests, traits, and skills
- Consider from the candidate’s perspective how well they would fit with the company
By following these practices, you can achieve an unbiased recruiting AI, making the hiring process much easier and fair. The AI can be trained to eliminate bias from the talent pool and identify the best potential hires. It can also be integrated with other applicant tracking systems and business software. This makes recruiting AI extremely valuable to the hiring process.
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Last Updated on February 10, 2021.