Bias is a normal part of human cognition. In order to make sense of the world, the human brain relies on a number of shortcuts, such as preferring people and items that are familiar (proximity bias) or relying on our memories even when memory is inaccurate (cognitive bias).
Although bias is normal, it is not always helpful. When unconscious biases are allowed to influence hiring decisions, the results can be detrimental for both the candidates and the company. To avoid these detrimental hiring effects, some companies have turned to blind hiring.
What is blind hiring?
Blind hiring seeks to remove all identifying information from candidates’ applications, leaving only details relevant to the job. For example, a blind hiring process might redact information like:
- Names, addresses, and phone numbers,
- Names of schools attended and years of attendance,
- Any other potentially identifying information.
Details that would still be available to the hiring team include:
- Education or training achieved,
- Job responsibilities and achievements in past roles,
- Descriptions of skills and the results of applying certain skills.
Benefits of blind hiring
The goal of blind hiring is to remove information that could influence the hiring team’s decisions, but that has nothing to do with the candidate’s ability to do the actual job. Done well, blind hiring can:
- Reduce the effects of unconscious bias by eliminating triggers for that bias,
- Focus the hiring team’s attention on the skills needed to perform well,
- Allow the team to compare skills directly for a clearer analysis of each candidate.
Blind hiring can pose challenges, as well. For instance, a hiring team will need a reliable way to redact identifying information without losing that information. You may not want to see names while reading resumes, but once you’ve chosen a few candidates to interview, you will need their names and contact information. Blind hiring also risks redacting too much, skewing the remaining data.
Other tools to reduce bias in hiring
Recent attention to bias in hiring has led to a variety of attempts to combat it. So far, no method is perfect. Each poses particular challenges and drawbacks. Artificial intelligence, for example, may simply replicate the biases present in its training data – especially if that data set is small or is drawn from a single source.
Yet businesses don’t have to wait for perfection in order to benefit from attempts to reduce bias. Blind hiring is one way a company can focus on the qualities that affect success in the role in order to find better candidates – and avoid committing impermissible discrimination.
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