AI is increasingly used to aid decision-making about the allocation of scarce societal resources, for example housing for homeless people, organs for transplantation, and food donations. Recently, there have been several proposals for how to design objectives for these systems that attempt to achieve some combination of fairness, efficiency, incentive compatibility, and satisfactory aggregation of stakeholder preferences. This paper lays out possible roles and opportunities for AI in this domain, arguing for a closer engagement with the political philosophy literature on local justice, which provides a framework for thinking about how societies have over time framed objectives for such allocation problems. It also discusses how we may be able to integrate into this framework the opportunities and risks opened up by the ubiquity of data and the availability of algorithms that can use them to make accurate predictions about the future.
翻译:AI越来越多地用于帮助决策分配稀缺的社会资源,例如无家可归者的住房、移植器官和食品捐赠。 最近,有人就如何设计这些体系的目标提出了几项建议,这些体系试图实现公平、效率、激励兼容性和利益攸关方喜好令人满意的组合。 本文阐述了AI在这一领域可能发挥的作用和机会,主张更密切地参与地方司法的政治哲学文献,该文献为思考社会如何随着时间的推移为此类分配问题设定目标提供了一个框架。 它还讨论了我们如何能够将数据多寡以及可用算法对未来作出准确预测所带来的机遇和风险纳入这一框架。