Hastings Cent Rep. 2021 Jan;51(1):8-9. doi: 10.1002/hast.1203. Epub 2020 Dec 14.
Artificial intelligence holds great promise for improved health-care outcomes. But it also poses substantial new hazards, including algorithmic discrimination. For example, an algorithm used to identify candidates for beneficial "high risk care management" programs routinely failed to select racial minorities. Furthermore, some algorithms deliberately adjust for race in ways that divert resources away from minority patients. To illustrate, algorithms have underestimated African Americans' risks of kidney stones and death from heart failure. Algorithmic discrimination can violate Title VI of the Civil Rights Act and Section 1557 of the Affordable Care Act when it unjustifiably disadvantages underserved populations. This article urges that both legal and technical tools be deployed to promote AI fairness. Plaintiffs should be able to assert disparate impact claims in health-care litigation, and Congress should enact an Algorithmic Accountability Act. In addition, fairness should be a key element in designing, implementing, validating, and employing AI.
人工智能有望改善医疗保健结果。但它也带来了新的重大风险，包括算法歧视。例如，用于识别有益的“高风险护理管理”计划候选人的算法经常未能选择少数民族。此外，一些算法故意以将资源从少数族裔患者转移走的方式调整种族。例如，算法低估了非裔美国人患肾结石和心力衰竭死亡的风险。当算法不合理地使服务不足的人群处于不利地位时，算法歧视可能会违反《民权法案》第六篇和《平价医疗法案》第 1557 条。本文敦促部署法律和技术工具来促进人工智能公平性。在医疗保健诉讼中，原告应该能够提出差异影响索赔，国会应该颁布《算法问责法》。此外，公平性应该是设计、实施、验证和使用人工智能的关键要素。
