Taking Algorithms to Courts: A Relational Approach to Algorithmic Accountability
Taking Algorithms to Courts: A Relational Approach to Algorithmic Accountability
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将算法告上法庭：算法问责的关系方法
DOI：
10.1145/3593013.3594092
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Watkins, Elizabeth Anne
中科院分区：
文献类型：
--
作者：
Metcalf, Jacob;Singh, Ranjit;Moss, Emanuel;Tafesse, Emnet;Watkins, Elizabeth Anne
在广泛使用的关于如何通过机构构建问责制的社会学描述中，“参与者”（例如开发者）对“论坛”（例如监管机构）负责，该“论坛”有权对参与者做出判断并要求参与者做出改变或实施制裁。然而，关于构建问责制的问题仍然存在：为什么以及如何在需要行为者提出要求时被迫不断向行为者提出要求？论坛在履行其职责时向谁负责？其做法和决定如何受到质疑？在算法问责的背景下，我们认为强大的问责制度需要三元关系，其中论坛还对另一个实体：公众负责。通常，与环境影响评估的情况一样，公众通过法院对论坛的判决和程序提出要求，从而建立尽职调查的最低标准。然而，与以下相关的核心挑战：(1) 缺乏文件，(2) 主张地位困难，以及 (3) 在对抗性诉讼中围绕算法系统的专家证据的可采性以及就算法系统的运作达成共识而展开的斗争，阻碍了公众在面临算法损害时向法院求助。在本文中，我们证明法院是寻求算法损害赔偿的主要途径和主要障碍。法院经常发现算法造成的损害是不可识别的，并且很少要求开发者解决重大损害索赔问题。为了解决将算法告上法庭的核心挑战，我们开发了一种算法问责的关系方法，该方法不强调参与者所做的事情或他们行为的结果，而是强调如何在参与者、论坛和公众之间的三元关系中构建问责关系。与其他监管领域的情况一样，我们认为影响评估（以及类似的问责文件）可以为各方之间的争论提供基础，但前提是该三方的结构使得公众能够围绕共同的经验和利益团结起来，对影响他们生活的算法系统的结果提出质疑，并对其他各方提出要求。如果法院现在发现算法危害无法识别，则影响评估制度可能会创造程序性权利来保护公众的实质性权利。这需要目前正在考虑的算法问责政策，为公众提供在法庭上足够的地位，以及访问和质疑行为者的文件和论坛判决的机会。
In widely used sociological descriptions of how accountability is structured through institutions, an “actor” (e.g., the developer) is accountable to a “forum” (e.g., regulatory agencies) empowered to pass judgements on and demand changes from the actor or enforce sanctions. However, questions about structuring accountability persist: why and how is a forum compelled to keep making demands of the actor when such demands are called for? To whom is a forum accountable in the performance of its responsibilities, and how can its practices and decisions be contested? In the context of algorithmic accountability, we contend that a robust accountability regime requires a triadic relationship, wherein the forum is also accountable to another entity: the public(s). Typically, as is the case with environmental impact assessments, public(s) make demands upon the forum's judgements and procedures through the courts, thereby establishing a minimum standard of due diligence. However, core challenges relating to: (1) lack of documentation, (2) difficulties in claiming standing, and (3) struggles around admissibility of expert evidence on and achieving consensus over the workings of algorithmic systems in adversarial proceedings prevent the public from approaching the courts when faced with algorithmic harms. In this paper, we demonstrate that the courts are the primary route—and the primary roadblock—in the pursuit of redress for algorithmic harms. Courts often find algorithmic harms non-cognizable and rarely require developers to address material claims of harm. To address the core challenges of taking algorithms to court, we develop a relational approach to algorithmic accountability that emphasizes not what the actors do nor the results of their actions, but rather how interlocking relationships of accountability are constituted in a triadic relationship between actors, forums, and public(s). As is the case in other regulatory domains, we believe that impact assessments (and similar accountability documentation) can provide the grounds for contestation between these parties, but only when that triad is structured such that the public(s) are able to cohere around shared experiences and interests, contest the outcomes of algorithmic systems that affect their lives, and make demands upon the other parties. Where courts now find algorithmic harms non-cognizable, an impact assessment regime can potentially create procedural rights to protect substantive rights of the public(s). This would require algorithmic accountability policies currently under consideration to provide the public(s) with adequate standing in courts, and opportunities to access and contest the actor's documentation and the forum's judgments.
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