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There’s never been more scholarship on hiring practices than in recent years, with the rise of artificial intelligence and machine learning as enhancements to some of recruitment’s most frustrating diversity challenges. Entire companies now offer a variety of data-backed products from video interviewing to AI-powered chat bots designed to remove decision fatigue and unconscious bias from talent acquisition practices. That said, science tells us that there is still value in utilizing a standard set of both situational and behavioral interview questions for all candidates, as a way to ensure a fair evaluation standards. Other practices, such as leveraging a diverse committee for talent hiring decisions (complete with “wildcard” members from outside the candidate’s proposed department with no subject-matter investment in the hiring decision) provide checks and balances against bias and tunnel-vision thinking. Ultimately, a talent strategy built with commitment to growing diversity through minimizing bias ensures you’re hiring the best people for each position, creating a more dynamic workforce that will fuel your bottom line.

Key Takeaways:

• Consider using AI-powered ATS systems to combat unconscious bias
• Distribute evaluation and decision-making authority among a diverse team

Perform an audit of your recruitment process w/ an eye toward questions — not solutions:

• Are your job postings created by software, or by humans? You’d be surprised how the use of gender-neutral pronouns can expand your talent pool.
• Do you leave decisions to the end of the day when employees are fatigued?
• Do you allow each interviewer to assess candidates or are there standard questions that are adhered to for fairness?