AI Jargon Buster
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What is Algorithmic Bias?
Algorithmic bias occurs when a computer system produces results that are systematically prejudiced due to errors in the data used to train it. Because AI learns from historical information, it often mirrors the human biases, social inequalities, or outdated practices present in that data. If a system is trained on records from a company that historically hired only one type of person, the AI may incorrectly conclude that those traits are requirements for success. This creates a cycle where the software reinforces past mistakes rather than making objective, neutral decisions.
Why this matters to you
It is critical because biased systems can lead to unfair treatment in hiring, lending, and performance reviews. Relying on these tools without oversight can damage your company reputation, lead to legal challenges, and prevent you from hiring the best talent for the job.
How you might hear this
We are conducting an audit to identify potential algorithmic bias in our new automated recruitment software.
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