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关于预测建模者和决策者:为什么公平需要不仅仅是一个公平的预测模型
Teresa Scantamburlo1, Joachim Baumann2,3, Christoph Heitz3
1Department of Environmental Sciences, Informatics and Statistics, European Centre for Living Technology, Ca' Foscari University, Via Torino 155, Room Z.B17, Building Z, 30172 Venezia-Mestre, Italy.
概括
本研究区分了预测和决策,以澄清算法公平性. 它提出了一个框架,通过定义不同的角色和责任,在基于预测的决策系统中实现公平.
科学领域:
- 计算机科学 计算机科学
- 人工智能的人工智能
- 伦理学 伦理学 伦理学
背景情况:
- 基于预测的决策领域经常将预测和决策混为一谈,导致实现算法公平性的模糊性.
- 现有文献经常使用"公平预测"一词,而不将其与后续决策系统的公平性区分开来.
研究的目的:
- 澄清算法系统中预测和决策之间的概念区别.
- 提出一个框架来理解和实施基于预测的决策中的公平性.
- 突出依赖上下文的公平的重要性以及不同参与者的角色.
主要方法:
- 概念分析区分预测和决策.
- 开发一个框架来分析算法决策系统中的公平性.
- 识别不同的角色 (预测建模者,决策者) 及其信息要求.
主要成果:
- 公平是决策系统的属性,而不仅仅是预测模型,因为它影响着人类的生活.
- 拟议的框架阐明了预测和决策要素如何影响整体系统的公平性.
- 预测建模者和决策者在实现公平性方面有明确的责任.
结论:
- 区分预测与决策对于有效的算法公平性实施至关重要.
- 拟议的框架有助于结构化公平考虑,分配责任,并建立治理机制.
- 将重点转移到与不同参与者的上下文依赖的算法决策对于现实世界的公平性至关重要.
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