STRETCHING HUMAN LAWS TO APPLY TO MACHINES: THE DANGERS OF A “COLORBLIND” COMPUTER

Automated decision making has become widespread in recent years, largely due to
advances in machine learning methods. As a result of this trend, automated systems are increasingly used in high-impact applications, such as university admissions decisions. The weightiness of these decisions has prompted the realization that, like humans, machines must also comply with the law. But the human decision-making process is quite different from the computational decision-making process, which creates a mismatch between the laws and the decision makers they were designed to apply to. This mismatch can lead to counterproductive outcomes. I take antidiscrimination laws in university admissions as a case example, with a
particular focus on Title VI of the Civil Rights Act of 1964.