如果我不喜欢任何一个选择呢？启发式算法设计的偏好获取限制
What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design
摘要：
参与式算法设计的新兴方法已经提出收集和汇总各个利益相关者的偏好，以创建考虑这些利益相关者的价值的算法系统。使用算法的学生分配作为一个案例研究，我们认为，优化个人偏好满足有限的资源分配实际上可能会抑制社会和分配正义的进展。个人偏好可以是一个有用的信号，但应加以扩大，以支持更有表现力和包容性的民主参与形式。
英文摘要：
Emerging methods for participatory algorithm design have proposed collecting and aggregating individual stakeholder preferences to create algorithmic systems that account for those stakeholders' values. Using algorithmic student assignment as a case study, we argue that optimizing for individual preference satisfaction in the distribution of limited resources may actually inhibit progress towards social and distributive justice. Individual preferences can be a useful signal but should be expanded to support more expressive and inclusive forms of democratic participation.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
