Fairness in Clustering

Anshuman discusses how historical bias affects clustering, leading to unfair outcomes for certain groups. Kyle explores the challenges of fairness in unsupervised learning, highlighting the need for careful consideration in model outputs. The conversation delves into the complexities of fairness definitions in different application scenarios.