Ensuring Fairness in Algorithmic Decision-Making

When using AI for candidate screening or ranking, it’s vital to build and audit algorithms to minimize existing biases that can perpetuate discrimination. Regularly checking datasets for representativeness and fairness helps promote an inclusive recruitment process, ensuring that AI doesn’t replicate or amplify historical inequities.

When using AI for candidate screening or ranking, it’s vital to build and audit algorithms to minimize existing biases that can perpetuate discrimination. Regularly checking datasets for representativeness and fairness helps promote an inclusive recruitment process, ensuring that AI doesn’t replicate or amplify historical inequities.

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