Reduce Bias in the Hiring Process

Our bias mitigation solution helps create equitable workforces that more closely match the demographics of the communities they serve.

Bias Mitigation

Biased hiring hurts both candidates and organizations by keeping qualified candidates from positions where they would thrive. That's why our platform uses a machine learning technique known as adversarial fairness—to avoid making biased predictions that amplify social bias.

  • Reduce bias in the hiring process

  • Increase equity and diversity

  • Improve workforce stability

Moving Past
Cognitive Shortcuts

Everyone has developed cognitive shortcuts as a necessary element of navigating everyday life. But these same shortcuts can prove unproductive at best and harmful at worst when making hiring decisions that require nuance and outside-the-box thinking. Arena helps employers hiring managers move past unconscious bias and discover a new, more objective and expansive lens through which to view talent.

Data Models

Our predictor model produces retention predictions for candidates, while our discriminator model analyzes the same data to identify demographic and related classification data.

Adversarial Fairness

By pitting these models against one another, Adversarial Fairness removes biased data points while delivering accurate retention predictions.

Unbiased Results

The result is unbiased data, with recommended hires surpassing the EEOC’s compliance threshold to create a hiring pool that mirrors the applicant pool.