Blog

Reducing Bias in the Workplace

07/08/2021

Sixty-three percent of companies are relying on training to improve diversity and reduce bias in the workplace. There’s a problem with that: Unconscious bias is built into human thinking. Training makes us aware of it, but it is impossible to remove unconscious bias completely from candidate selection and hiring decisions.

Artificial intelligence (AI) technologies can help you bring a more effective solution to your organization. If your recruiting team is accountable for reducing bias and increasing fairness in your hiring process, here are the questions you should be asking:

How does AI reduce bias and increase fairness in hiring?

The practical application of advanced AI techniques in Modern Hire’s science-based virtual hiring platform elevates the standard of fairness by identifying and mitigating bias in pre-hire assessments. Modern Hire’s pre-hire assessments evaluate candidates on job-specific core competencies using algorithms that have been designed, tested and proven to minimize bias. The models can interpret data from multiple sources, including situational judgment exercises, personality type scales, and unstructured data from text responses. As a result, recruiters using Modern Hire’s platform gain job performance prediction and diversity of hiring at levels far above current industry standards.

Modern Hire also offers the industry’s leading solution for overcoming interview bias. Automated Interview Scoring uses AI to evaluate candidate responses to on-demand interview questions and provide hiring teams with recommended scores. It is proven to combat interview bias and ensure fairer, more effective hiring decisions.

Can AI give unfair results?

Yes, there have been well-documented cases which indicate AI can produce biased results. Concerns about unfair results due to AI in hiring have been solidified by missteps like the use of AI-enabled facial recognition during video interviews, and AI tools that score candidates based on resumes. (Resumes are a low-value data source for predicting candidates’ future job performance.)

Even the perceptions of unfairness in a company’s hiring practices or that AI is

invading candidate privacy can create a poor candidate experience and damage the company’s employer brand. Fairness in hiring must be a priority.

How can we ensure our hiring process minimizes bias?

There are several ways you can be proactive to do this:

  • Choose an AI hiring partner with a track record of sound science and can explain to you in plain language what data is collected, how it is collected, and how it is used to support less biased, more informed hiring decisions
  • Track diversity metrics and use analytics to evaluate your hiring process. Evaluation is the starting point for identifying issues and prioritizing solutions for increasing fairness in hiring. For a list of suggested diversity metrics download Redefining Success: Talent Analytics For The Future.
  • Adopt a policy on the ethical application of AI in hiring. A well-considered policy can help inform hiring process improvements and guide decisions about your process, such as how and when to inform candidates about the use of AI in hiring. It can also guide decisions about hiring technologies in the direction of fairer hiring. View Modern Hire’s Principles for the Ethical Application of AI to Candidate Selection.

For practical information on selecting an AI hiring partner, download the Modern Hire Buyer’s Guide to AI-Driven Hiring. It will help ensure the AI-powered technology you choose will accelerate the reduction of bias in your workplace.