4 Major Effects Of AI On Recruiting & Diversity

While AI for recruiting’s primary function is to streamline or automate some part of the the workflow especially repetitive, time consuming tasks, one intriguing benefit is its potential to minimize unconscious bias.

ai and diversityHere are 4 mechanisms on how AI is reducing bias in recruiting and its effect on diversity.

1. Job Postings  

An AI technique called sentiment analysis can identify exclusionary language (e.g., aggressive, competitive, brilliant) that research has found may turn off certain groups of candidates.

For example, studies by researchers at the University of Waterloo has found job postings that use adjectives like aggressive and competitive attract fewer female candidates.

New research on job ads found women were less interested in applying to roles that included brilliance-related descriptions compared to dedication-related ones such as “passionate about the job”.

The technology suggests alternatives that are more inclusive in order to attract a more diverse candidate pool such as “committed” and “responsible.”

2. Sourcing

AI is being used to find candidates online or within resume databases such as CareerBuilder by learning the qualifications of a role from a job description.

Studies conducted at the University of Toronto found Asian applicants were 75% more likely to receive an interview when they used a “whitened” version of their name on their resume. Example: Luke instead of Lu. Black applicants were 160% more likely to receive an interview if they used a “whitened” version of their name.

AI can bypass  this type of unconscious bias because it can be programmed to ignore demographic information such as race, age, & gender as implied by a candidate’s name or graduation dates.

3. Resume Screening

AI can automate resume screening by learning what your existing employees’ qualifications are and applying this knowledge to screen and grade new candidates (e.g., A to D).

Similar to sourcing, the AI can be programmed to ignore demographic information to help avoid unconscious bias that research has shown can lead to discrimination at the screening phase.

4. Messaging

Via SMS, email, or through your career website, a chatbot can ask screening questions, answer FAQs, and even schedule an interview simultaneously with hundreds to thousands of candidates in real time.

Chatbots can greatly reduce a recruiter’s workload because the information it collects can be fed into your ATS or sent directly to a human recruiter to follow up.

A recruiting chatbot can decrease bias in recruiting by providing consistent and objective treatment and communication with candidate.

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Ji-A Min

Ji-A Min

Head Data Scientist at Ideal
Ji-A Min is the Head Data Scientist at Ideal. With a Master’s in Industrial-Organizational Psychology, Ji-A promotes best practices in data-based recruitment. She writes about research and trends in talent acquisition, recruitment tech, and people analytics.
Ji-A Min

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