What is an Algorithmic Bias Audit? | AI Jargon Buster | Monard X
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AI Policy and Regulation

What is an Algorithmic Bias Audit?

An algorithmic bias audit is a structured evaluation where internal teams or outside experts examine an AI system to find patterns of unfairness. These systems often learn from historical data that contains human prejudices, which can lead the software to favor certain groups over others. During an audit, testers look for evidence of discrimination in how the system makes decisions. The process involves reviewing the data used to train the model, checking the logic of the software, and analyzing the final results to ensure the system treats all people fairly and follows ethical standards.

Why this matters to you

Performing these audits helps your organization avoid costly lawsuits and public scandals. It ensures that your automated tools do not accidentally exclude qualified candidates or deny services to specific groups, which builds trust with your customers and employees.

How you might hear this

Our legal department requires an algorithmic bias audit before we can launch this new hiring tool.

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