Binary Governance: Lessons from the GDPR's Approach to Algorithmic Accountability
Binary Governance: Lessons from the GDPR's Approach to Algorithmic Accountability
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二元治理：GDPR 算法问责方法的经验教训
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发表时间：
2019
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通讯作者：
M. Kaminski
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作者：
M. Kaminski
算法现在被用来做出关于个人的重要决定，从信用决定到雇佣和解雇。但它们在很大程度上不受美国法律的监管。关于如何解决算法决策的问题，迅速增长的文献出现了分歧，个人权利和对非专家利益相关者和公众的责任是辩论的核心。在这篇文章中，我提出了为什么个人权利和公众和利益相关者面对的问责制不仅仅是商品本身，而是有效治理的关键组成部分。只有个人权利才能完全解决规范算法决策的呼吁背后的重要和正当性问题。如果没有某种形式的公共和利益相关者问责制，公私合作的算法系统治理方法将失败。
在这篇文章中，我确定了规范算法决策的呼吁背后的三种担忧：尊严，正当性和工具性。尊严的关注导致我们监管算法以保护人类尊严和自主权的建议;正当性的关注警告我们必须评估算法推理的合法性;工具性的关注导致要求监管以防止随之而来的问题，如错误和偏见。没有任何一种监管办法可以有效地解决所有这三个问题。因此，我提出了一种双管齐下的算法治理方法：个人正当程序权利体系与通过合作治理（使用公私伙伴关系）实现的系统性监管相结合。只有通过这种二元方法，我们才能有效地解决算法决策或人工智能（“AI”）决策所引起的所有三个问题。
这两种方法之间的相互作用将是复杂的。这两种制度有时是互补的，有时又是紧张的。欧盟的《通用数据保护条例》（GDPR）就是这样一个二元体系。我探讨了GDPR的广泛协作治理方面，以及它们如何与其个人权利制度相互作用。以这种方式理解GDPR既阐明了其优势和劣势，也为如何构建更好的治理制度提供了一个模型，以实现负责任的算法或人工智能决策。它还表明，在缺乏公共和利益攸关方问责制的情况下，个人权利可以在建立合作制度的合法性方面发挥重要作用
Algorithms are now used to make significant decisions about individuals, from credit determinations to hiring and firing. But they are largely unregulated under U.S. law. A quickly growing literature has split on how to address algorithmic decision-making, with individual rights and accountability to nonexpert stakeholders and to the public at the crux of the debate. In this Article, I make the case for why both individual rights and public- and stakeholder-facing accountability are not just goods in and of themselves but crucial components of effective governance. Only individual rights can fully address dignitary and justificatory concerns behind calls for regulating algorithmic decision-making. And without some form of public and stakeholder accountability, collaborative public-private approaches to systemic governance of algorithms will fail.
In this Article, I identify three categories of concern behind calls for regulating algorithmic decision-making: dignitary, justificatory, and instrumental. Dignitary concerns lead to proposals that we regulate algorithms to protect human dignity and autonomy; justificatory concerns caution that we must assess the legitimacy of algorithmic reasoning; and instrumental concerns lead to calls for regulation to prevent consequent problems such as error and bias. No one regulatory approach can effectively address all three. I therefore propose a two-pronged approach to algorithmic governance: a system of individual due process rights combined with systemic regulation achieved through collaborative governance (the use of private-public partnerships). Only through this binary approach can we effectively address all three concerns raised by algorithmic decision-making, or decision-making by Artificial Intelligence (“AI”).
The interplay between the two approaches will be complex. Sometimes the two systems will be complementary, and at other times, they will be in tension. The European Union’s (“EU’s”) General Data Protection Regulation (“GDPR”) is one such binary system. I explore the extensive collaborative governance aspects of the GDPR and how they interact with its individual rights regime. Understanding the GDPR in this way both illuminates its strengths and weaknesses and provides a model for how to construct a better governance regime for accountable algorithmic, or AI, decision-making. It shows, too, that in the absence of public and stakeholder accountability, individual rights can have a significant role to play in establishing the legitimacy of a collaborative regime