How can statistical discrimination impact individual assessments?

Statistical discrimination refers to the practice of making assumptions about an individual based on the characteristics of the group to which they belong, rather than their individual merits. This can lead to unfair conclusions during assessments, as decisions are influenced by stereotypes or averages associated with certain demographic categories rather than an objective evaluation of an individual’s capabilities or achievements.

In settings such as hiring, lending, or medical assessments, statistical discrimination can skew outcomes by leading evaluators to overlook qualified candidates or individuals, assuming they possess negative attributes solely based on group characteristics such as race, gender, or socioeconomic status. This undermines fairness and equity, ultimately affecting the opportunities and treatment individuals receive in various domains of life. The other options suggest positive outcomes that are not characteristic of statistical discrimination, which highlights why this concept leads to detrimental effects on individual assessments.