Proxies

Abstract

Calculating Race’s fourth chapter demonstrates that race has become so highly correlated with other social statistics that actuarial science in general has developed a baked-in racial bias. Racial discrimination by proxy (e.g., zip code standing in for race) can be glimpsed in the disparate impact of data-driven decision-making in housing, healthcare, policing, sentencing, and more. Simply leaving out racial data in statistically aided decision-making distances institutions from claims of intentional discrimination, but a disparate, discriminatory impact lingers when other factors correlated with race power actuarial analyses. Chapter 4 considers how insurance law in the United States has defined the limits of acceptable discrimination. By surveying the progression of state-by-state regulations that prohibit or accept the use of race, gender, sex, sexuality, ability, age, and genetics in an industry that revolves around the ability to discriminate risk, it uncovers who the United States has historically chosen to protect.