论文标题
算法求程的调查：定义，配方，解决方案和前景
A survey of algorithmic recourse: definitions, formulations, solutions, and prospects
论文作者
论文摘要
机器学习越来越多地用于在敏感情况下为决策带来对个人生活的影响。在这些环境中，除了要求模型必须是准确且稳健的，与公平，隐私，问责制和解释性等社会相关价值观，对所述技术的采用和影响也是重要的作用。在这项工作中，我们专注于算法追索权，这与为受自动决策系统不利的个人提供解释和建议。我们首先进行了广泛的文献综述，并通过提出统一的定义，表述和追索性解决方案来使许多作者的努力保持一致。然后，我们概述了社区可以参与的前瞻性研究方向，挑战现有的假设并与其他道德挑战（例如安全，隐私和公平性）建立明确的联系。
Machine learning is increasingly used to inform decision-making in sensitive situations where decisions have consequential effects on individuals' lives. In these settings, in addition to requiring models to be accurate and robust, socially relevant values such as fairness, privacy, accountability, and explainability play an important role for the adoption and impact of said technologies. In this work, we focus on algorithmic recourse, which is concerned with providing explanations and recommendations to individuals who are unfavourably treated by automated decision-making systems. We first perform an extensive literature review, and align the efforts of many authors by presenting unified definitions, formulations, and solutions to recourse. Then, we provide an overview of the prospective research directions towards which the community may engage, challenging existing assumptions and making explicit connections to other ethical challenges such as security, privacy, and fairness.
