What Is A Bias Audit? The Simple Definition
A bias audit is a review process to check if an AI system’s decisions or predictions are unfairly favoring or discriminating against specific groups based on factors like race or gender. The type and nature of the bias will depend on the context of the model and how it is used. FairNow automates the bias audit process to ensure models are always operating responsibly.
The Technical Definition
A bias audit is a systematic assessment of an AI system’s behavior and decision-making processes to identify and quantify any biases or unfairness in its outcomes, particularly in relation to sensitive attributes such as race, gender, age, or other protected characteristics. It involves analyzing data, algorithms, and model outputs to determine the presence and extent of bias, followed by corrective measures to mitigate or eliminate such biases, ensuring equitable and fair results.
Bias audits are crucial for maintaining transparency, fairness, and ethical standards in AI systems.
Explain It Like I’m Five
A bias audit is like a detective checking if a computer program is being unfair to different people. It looks for signs that the program might be treating some people better or worse based on things like their skin color or gender. If it finds any unfairness, it helps fix it so that the program is fair to everyone.
Use It At The Water Cooler
How to use “bias audit” in a sentence at work:
“We conducted a thorough bias audit of our AI-powered hiring system to ensure that it doesn’t favor any specific group of candidates and maintains fairness in our recruitment process.”