Stretching Human Laws to Apply to Machines: The Dangers of a 'Colorblind' Computer - Harned, Zach; Wallach, Hanna (Florida State University Law Review, Forthcoming, 2019)
Automated decision making has become widespread in recent years, largely due to advances in machine learning. As a result of this trend, machine learning systems are increasingly used to make decisions in high-stakes domains, such as employment or university admissions. The weightiness of these decisions has prompted the realization that, like humans, machines must also comply with the law. But human decision-making processes are quite different from automated decision-making processes, which creates a mismatch between laws and the decision makers to which they are intended to apply. In turn, this mismatch can lead to counterproductive outcomes.