Accountable Algorithms
Accountable Algorithms
复制标题
负责任的算法
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
Harlan YUt
中科院分区：
文献类型：
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作者：
J. Reidenberg;J. Reidenberg;D. G. Robinson;Harlan YUt
历史上许多重要的决策都是由人来做的，现在都由计算机来做。算法计算选票，批准贷款和信用卡申请，针对公民或社区进行警察审查，选择纳税人进行国税局审计，授予或拒绝移民签证等等。管理这种决策过程的问责机制和法律的标准没有跟上技术的步伐。政策制定者、立法者和法院目前可用的工具是为了监督人类决策者而开发的，当应用于计算机时往往会失败。例如，你如何判断一个软件的意图？由于自动化决策系统可能会返回潜在的不正确、不合理或不公平的结果，因此需要采取其他方法来使此类系统变得可问责和可治理。本文揭示了一种新的技术工具包，用于验证自动化决策是否符合法律的公平性的关键标准。我们对法律的文献中认为透明度将解决这些问题的主导地位提出质疑。披露源代码通常既不必要（因为计算机科学的替代技术），也不足以（因为分析代码的问题）证明过程的公平性。此外，透明度
Many important decisions historically made by people are now made by computers. Algorithms count votes, approve loan and credit card applications, target citizens or neighborhoods for police scrutiny, select taxpayers for IRS audit, grant or deny immigration visas, and more. The accountability mechanisms and legal standards that govern such decision processes have not kept pace with technology. The tools currently available to policymakers, legislators, and courts were developed to oversee human decisionmakers and often fail when applied to computers instead. For example, how do you judge the intent of a piece of software? Because automated decision systems can return potentially incorrect, unjustified, or unfair results, additional approaches are needed to make such systems accountable and governable. This Article reveals a new technological toolkit to verify that automated decisions comply with key standards of legal fairness. We challenge the dominant position in the legal literature that transparency will solve these problems. Disclosure of source code is often neither necessary (because of alternative techniques from computer science) nor sufficient (because of the issues analyzing code) to demonstrate the fairness of a process. Furthermore, transparency