Reduce Bias And Increase Diversity

ideal's bias reduction features

AI ignores demographic-related information such as the candidate’s name, race, sex, and age during screening and shortlisting.

Ensure Compliance

Ideal’s proprietary AI for recruiting technology is both EEOC and OFCCP compliant.

Reduce Bias

Biases in the screening process can unknowingly eliminate great candidates. Make data-backed hiring decisions based on merit. 

Increase Diversity

Diversity is a competitive advantage. Increase your workplace diversity and build stronger teams.

How We Do It

Workplace diversity has become a competitive recruiting advantage. 67% of job seekers consider a company’s diversity to be an important factor when considering job offers.

A significant barrier to increasing diversity is unconscious bias during the recruiting process.

Research suggests that bias in the form of adverse impact (i.e., a substantially different rate of selection in hiring that disadvantages members of a race, sex or ethnic group) can happen during resume screening:

  • Resumes with white-sounding names receive requests for interviews 50 percent more often than identical resumes with African American-sounding names
  • Resumes with English-sounding names receive requests for interviews 40 percent more often than identical resumes with Chinese, Indian, or Pakistani names
  • Resumes with male names receive requests for interviews 40 percent more often than similar resumes with female names

Ideal’s AI can help reduce bias by excluding demographic data such as the candidate’s race, sex, and age and data correlated with demographics (e.g., names, zip codes) during its screening decision making.

If your organization collects demographic data for the race, sex, and ethnic group of your applicants, Ideal can further avoid bias during screening using two options:

  1. Ideal can perform backtests on its candidate grades for adverse impact (based on EEOC’s 4/5ths rule) using the employer’s historical hiring decisions.
  2. Ideal can monitor its candidate grades by assessing the percentages of the race, sex, and ethnic group of candidates and removing any identified bias to remain EEOC and OFCCP compliant.

By reducing bias at both the candidate sourcing and screening phase, Ideal’s AI helps remove an important barrier to diversity at the beginning of the recruiting cycle.