How can I evaluate bias in AI systems?
Evaluating bias in AI systems involves several steps, including data analysis, model testing, and fairness metrics.
What specific metrics should I use to measure bias?
Common metrics include demographic parity, equal opportunity, and disparate impact. Each measures different aspects of fairness.
Can you give an example of how to apply these metrics?
Sure! For instance, if you're assessing a hiring algorithm, you can compare the selection rates of different demographic groups using demographic parity.
What tools can help me in this evaluation process?
There are several tools like Fairness Indicators, AIF360, and What-If Tool that can assist in evaluating AI bias.
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