无人驾驶公司?

J. Armour, Horst Eidenmueller
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引用次数: 14

摘要

人工智能(AI)对公司法有什么影响?在本文中,我们考虑了人工智能的发展轨迹,分析了其应用对商业实践的影响,并调查了这些发展对公司法的影响。总的来说,我们声称人工智能在企业中的日益使用意味着将企业从主要视为私人和便利的转变为更公开和监管的企业活动法律概念。今天的人工智能主要由机器学习应用程序主导,这些应用程序可以帮助和增强人类的决策。这些给业务组织带来了多重挑战,我们将其统称为“数据治理”。今天的人工智能对公司法的影响将从两个方面体现出来。首先,我们期望在内部机构和协调成本的许多标准方面有所减少。其次,公司高层面临的监管挑战和责任风险将显著上升。未来的人工智能可能会让人类甚至在企业决策的最高层被取代。这很可能首先发生在我们所说的“自动驾驶子公司”中,它们的企业职能非常有限。用机器取代公司董事会中的人意味着焦点的根本转变:从控制内部成本到设计适当的策略来控制“算法故障”,即算法的非法行为可能对外部第三方产生严重的负面影响(身体或财务伤害)。我们讨论了企业目标设定,从中期来看,这可能成为人工智能和公司法辩论的焦点。随着技术进步,完全自动驾驶公司的可能性越来越大,这种情况只会加剧。我们概述了控制它们的潜在监管策略。监管竞争的可能性削弱了立法者的反应能力,因此,尽管自动驾驶公司尚未成为现实,但我们认为,在明天的人工智能成为今天的人工智能之前,监管问题值得关注。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Self-Driving Corporations?
What are the implications of artificial intelligence (AI) for corporate law? In this essay, we consider the trajectory of AI’s evolution, analyze the effects of its application on business practice, and investigate the impact of these developments for corporate law. Overall, we claim that the increasing use of AI in corporations implies a shift from viewing the enterprise as primarily private and facilitative, towards a more public, and regulatory, conception of the law governing corporate activity. Today’s AI is dominated by machine learning applications which assist and augment human decision-making. These raise multiple challenges for business organization, the management of which we collectively term ‘data governance’. The impact of today’s AI on corporate law is coming to be felt along two margins. First, we expect a reduction across many standard dimensions of internal agency and coordination costs. Second, the oversight challenges — and liability risks — at the top of the firm will rise significantly. Tomorrow’s AI may permit humans to be replaced even at the apex of corporate decision-making. This is likely to happen first in what we call ‘self-driving subsidiaries’ performing very limited corporate functions. Replacing humans on corporate boards by machines implies a fundamental shift in focus: from controlling internal costs to the design of appropriate strategies for controlling ‘algorithmic failure’, i.e. unlawful acts by an algorithm with potentially severe negative effects (physical or financial harm) on external third parties. We discuss corporate goal-setting, which in the medium term is likely to become the center of gravity for debate on AI and corporate law. This will only intensify as technical progress moves toward the possibility of fully self-driving corporations. We outline potential regulatory strategies for their control. The potential for regulatory competition weakens lawmakers’ ability to respond, and so even though the self-driving corporation is not yet a reality, we believe the regulatory issues deserve attention well before tomorrow’s AI becomes today’s.
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