Algorithmic fairness metrics are quantitative measures used to evaluate the fairness of algorithms, particularly those employed in decision-making processes. These metrics help assess whether an algorithm treats different demographic groups equitably, revealing any biases that may exist in the data or the model itself. By analyzing these metrics, stakeholders can ensure greater transparency and accountability in AI systems, which is crucial for fostering trust and ethical use of technology.
congrats on reading the definition of algorithmic fairness metrics. now let's actually learn it.