Diskriminatori
Diskriminatori refers to a concept in the field of artificial intelligence and machine learning, specifically within the context of bias detection and fairness in algorithms. The term originates from the idea of identifying and quantifying discriminatory patterns or biases embedded within machine learning models. These biases can arise from skewed training data, algorithmic design, or societal prejudices reflected in the data used to train models.
The process of diskriminatori involves analyzing how a model treats different groups of individuals or entities.
Common techniques in diskriminatori include statistical testing, fairness-aware algorithms, and auditing tools designed to detect discriminatory
While diskriminatori helps uncover unintended biases, it also raises ethical questions about accountability and the limits