The Alignment Problem: Machine Learning and Human Values

Christian (The Most Human Human), a writer and lecturer on technology-related issues, delivers a riveting and deeply complex look at artificial intelligence and the significant challenge in creating computer models that “capture our norms and values.” Machines that use mathematical and computational systems to learn are everywhere in modern life, Christian writes, and are “steadily replacing both human judgment and explicitly programmed software” in decision-making. Some of those decisions, however, are unreliable, as Christian shows through scrupulous research. Facial recognition systems can be “wildly inaccurate for people of one race or gender but not another” and perform particularly poorly on identifying Black women correctly. Meanwhile, risk assessment software, which helps decide bail, parole, and even sentencing for criminal defendants, has been widely adopted nationwide without being extensively audited. Though it’s tempting to assume a doom-and-gloom outlook while reading of these problems, Christian refreshingly insists that “our ultimate conclusions need not be grim,” as a new subset of computer scientists “focused explicitly on the ethics and safety of machine-learning” is working to bridge the gap between human values and AI learning styles. Lay readers will find Christian’s revealing study to be a helpful guide to an urgent problem in tech. (Oct.)