BLACK BOX TINKERING: Beyond Disclosure in Algorithmic Enforcement
BLACK BOX TINKERING: Beyond Disclosure in Algorithmic Enforcement
复制标题
黑匣子修补：算法执行中的超越披露
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
N. Elkin
中科院分区：
文献类型：
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作者：
Maayan Perel;N. Elkin
算法执行的普遍增长放大了当前关于透明度优点的辩论。使用代码进行强有力的在线执法不仅放大了已解决的问题，也就是通常与当今的披露有关的“信息过多”问题，而且在依赖透明度作为对算法执行的充分检查方面也带来了额外的实际困难。在这篇文章中，我们探索了黑箱修补方法的优点，作为在在线执法的算法系统中产生问责的手段。鉴于在线内容的算法强制执行对公共话语和基本权利的深远影响，我们主张积极让公众参与检查自动执行系统的做法。相应地，我们解释了产生公共监督的透明度不足的原因。首先，很难阅读、跟踪和预测算法背后的复杂计算机代码，因为它本质上是不透明的，并且能够根据不同的数据模式演变。其次，强制性的透明度要求与许多受贸易保密约束的算法治理的私人实现无关。第三，算法治理是如此强大，即使没有强制性的透明度，也不可能审查已经披露的所有信息。第四，当算法被要求在涉及自由裁量权的决定中取代人类时，算法的输入(事实)和输出(结果)的透明度不足以允许充分的监督。这是因为给定的法律结果不一定能提供关于其背后理由的充分信息。随后，我们利用最近一项关于在线中介机构在线版权执法实践的研究，将黑匣子修补的好处确立为一种鼓励社会激进主义的积极方法。这项研究试图通过检查流行的本地图像共享平台和流行的本地视频共享平台的行为，系统地测试托管网站如何执行版权政策。特别是，不同类型的侵权、非侵权和合理使用材料被上传到各种托管设施，每一种材料都旨在追踪黑匣子系统在整个执法过程中所做的选择。这项研究的结果表明，托管平台在检测在线侵权和执行版权方面是不一致的，因此不可预测：一些平台允许其他平台过滤的内容；一些平台严格回应任何要求删除内容的通知，尽管这些内容显然没有侵权，而其他平台在收到指控侵权通知后没有删除内容。此外，许多在线算法版权执法机制在尽量减少错误和确保相关方不滥用系统以压制合法言论和过度执行版权方面通常做得很少。最后，调查结果表明，在线平台没有尽全力确保正当程序，并允许受影响的个人遵循并迅速响应管理其在线提交的程序。基于这些发现，我们得出结论，黑匣子修补方法可以提供宝贵的实地算法执行实践的掌握。因此，我们评估了这一方法可能产生的法律影响，并提出了解决这些问题的方法。
The pervasive growth of algorithmic enforcement magnifies current debates regarding the virtues of transparency. Not only does using codes to conduct robust online enforcement amplify the settled problem of magnitude, or “too-much-information,” often associated with present-day disclosures, it imposes additional practical difficulties on relying on transparency as an adequate check for algorithmic enforcement. In this Essay we explore the virtues of black box tinkering methodology as means of generating accountability in algorithmic systems of online enforcement. Given the far-reaching implications of algorithmic enforcement of online content for public discourse and fundamental rights, we advocate active public engagement in checking the practices of automatic enforcement systems.Accordingly, we explain the inadequacy of transparency in generating public oversight. First, it is very difficult to read, follow and predict the complex computer code which underlies algorithms as it is inherently non-transparent and capable of evolving according to different patterns of data. Second, mandatory transparency requirements are irrelevant to many private implementations of algorithmic governance which are subject to trade secrecy. Third, algorithmic governance is so robust that even without mandatory transparency it is impossible to review all the information already disclosed. Fourth, when algorithms are called on to replace humans in making determinations that involve discretion, transparency about the algorithms’ inputs (the facts) and outputs (the outcomes) is not enough to allow adequate oversight. This is because a given legal outcome does not necessarily yield sufficient information about the reasoning behind it. Subsequently we establish the benefits of black box tinkering as a proactive methodology that encourages social activism, using the example of a recent study of online copyright enforcement practices by online intermediaries. That study sought to test systematically how hosting websites implement copyright policy by examining the conduct of popular local image-sharing platforms and popular local video-sharing platforms. Particularly, different types of infringing, non-infringing and fair use materials were uploaded to various hosting facilities, each intended to trace choices made by the black box system throughout its enforcement process. The study’s findings demonstrate that hosting platforms are inconsistent, therefore unpredictable in detecting online infringement and enforcing copyrights: some platforms allow content that is filtered by others; some platforms strictly respond to any notice requesting removal of content despite its being clearly non-infringing, while other platforms fail to remove content upon notice of alleged infringement. Moreover, many online mechanisms of algorithmic copyright enforcement generally do very little in terms of minimizing errors and ensuring that interested parties do not abuse the system to silence legitimate speech and over-enforce copyright. Finally, the findings indicate that online platforms do not make full efforts to secure due process and allow affected individuals to follow, and promptly respond to, proceedings that manage their online submissions.Based on these findings, we conclude that black box tinkering methodology could offer an invaluable grasp of algorithmic enforcement practices on the ground. We hence evaluate the possible legal implications of this methodology and propose means to address them.